References

@article{stoimenov2024the,

title = {The Integration of Explainable AI Methods for the Classification of Medical Image Data},

author = {M. Nikoli\'{c} and D. Jankovi\'{c} and A. Stanimirovi\'{c} and L. Stoimenov},

year  = {2024},

date = {2024-01-01},

journal = {2024 11th International Conference on Electrical, Electronic and Computing Engineering (IcETRAN), Nis, Serbia},

volume = {10.},

pages = {1\textendash6},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Rajkovi\'{c}202440,

title = {The Implementation of Battery Charging Strategy for IoT Nodes},

author = {Petar Rajkovi\'{c} and Dejan Aleksi\'{c} and Dragan Jankovi\'{c}},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190975465\&doi=10.1007%2f978-3-031-48803-0_4\&partnerID=40\&md5=7676ff6815a5ed637565141f7e867009},

doi = {10.1007/978-3-031-48803-0_4},

year  = {2024},

date = {2024-01-01},

journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},

volume = {14352 LNCS},

pages = {40 \textendash 51},

publisher = {Springer Science and Business Media Deutschland GmbH},

abstract = {The Internet of Things (IoT) nodes dedicated to off-grid usage must fully rely on their battery power for continuous operation. In that sense battery charging process design is one of the focal points for the complete system design. Nowadays, battery charging, for such devices, usually relies on solar power which is not, unfortunately, the source of constant energy. Both environmental and constructive elements could easily make a negative impact on the charging process and reduce the amount of collected energy. Furthermore, if the IoT nodes are in hazardous areas, they are less accessible, and the value of effective battery management is even higher. The requirements for the battery charging process implementation are considered as opposite \textendash on one hand, the requirement is to run charging with the lowest possible frequency and not up to 100%, and on the other hand, the battery should always have enough energy to maintain regular operation. In this research, we present the structure of the custom-developed IoT node based on the ECS32 system-on-a-chip dedicated to operating in remote industrial areas, and with an accent of its battery charging routine. The current routine is based on a standard thresholds approach and improved by including consumption estimates for the predefined periods. This paper presents the first results and should pave the ground for further upgrades. In addition, the comparison with state-of-the-art charging approaches is presented, as the guidelines for future work. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Avdi\'{c}202215,

title = {Smart Health Services Based on IoT and GIS},

author = {Aldina Avdi\'{c} and Ulfeta Marovac and Dragan Jankovi\'{c}},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130250188\&doi=10.1007%2f978-3-030-96627-0_2\&partnerID=40\&md5=2abbb85785a6fe47c75d473873a18ee5},

doi = {10.1007/978-3-030-96627-0_2},

year  = {2022},

date = {2022-01-01},

journal = {Studies in Computational Intelligence},

volume = {1026},

pages = {15 \textendash 23},

publisher = {Springer Science and Business Media Deutschland GmbH},

abstract = {Today, computer systems have the ability to access numerous user context data at any time, e.g. about its location, movement, habits, and other data that can be collected from sensors on mobile devices. This data can be processed and used for various purposes in the form of applications that can improve interaction with the user. Of particular importance are the purposes for providing health services. This paper proposes, describes, and provides an overview of the implementation of five smart health services based on the Internet of Things (IoT) and geographic information systems (GIS), namely: finding the nearest health care facilities, air quality monitoring, improving medical services, smart transport for patients, and mobile SOS system. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Rajkovi\'{c}2022,

title = {Hybrid Software Deployment Strategy for Complex Industrial Systems},

author = {Petar Rajkovi\'{c} and Dejan Aleksi\'{c} and Andjelija Djordjevi\'{c} and Dragan Jankovi\'{c}},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136449967\&doi=10.3390%2felectronics11142186\&partnerID=40\&md5=b358ea9f0778eb1fb37ba776a0bdb1d1},

doi = {10.3390/electronics11142186},

year  = {2022},

date = {2022-01-01},

journal = {Electronics (Switzerland)},

volume = {11},

number = {14},

publisher = {MDPI},

abstract = {Complex industrial systems run the different pieces of software in several interconnected physical layers. The software update in such an environment must be performed in the shortest possible period with the lowest possible resource usage. Namely, it is critical to minimize the data traffic, decrease software downtime, and reduce the impact of the transitional stage during the update process. To meet these requirements and to unify the update process, the common software node structure along with a hybrid software deployment strategy is proposed. The hybrid strategy is defined as a combination of the existing and well-tested techniques\textemdashblue/green, canary, and feature flags. The main aim was to utilize their positive sides and to obtain a better overall effect. The approach was tested in the simulation environment, based on the realistic factory layout, and running the software related to the enterprise resource planning (ERP) level. For successful updates, the proposed hybrid deployment method reduced downtime on server nodes to less than 5% and on client nodes to a half compared with the standard approach. The volume of data traffic reduction in a configuration with sentinel nodes is reduced by one-third. The presented results look promising, especially in cases of erroneous updates when a roll back is needed, where the downtime on the server nodes is reduced to the level of 3%. Achieved results are used to define the set of recommendations that could be extended for the other software layers, followed by a discussion about further potential problems and strategy variations. © 2022 by the authors.},

note = {All Open Access, Gold Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Spasic2022824,

title = {Programme-Sensitive Modifications of Generalized Net Model of Software-Intensive Production of Stereoscopic Multimedia Content},

author = {A. J. Spasic and D. S. Jankovic and P. J. Rajkovic and D. S. Aleksic},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139480775\&doi=10.1134%2fS1064230722050136\&partnerID=40\&md5=5304b5762cb204daeb26566995dd40ab},

doi = {10.1134/S1064230722050136},

year  = {2022},

date = {2022-01-01},

journal = {Journal of Computer and Systems Sciences International},

volume = {61},

number = {5},

pages = {824 \textendash 842},

publisher = {Pleiades journals},

abstract = {Abstract: The main goal of this paper is to show how it is possible to modify a previously created model of a software-intensive system for the production of stereoscopic multimedia content defined by generalized nets (GN) without disturbing its static structure. When the system is structurally complex, any disruption of the static structure of the system can produce side effects on the rest of the system’s functionality. Generalized nets, as a powerful theoretical mathematical tool widely accepted for modeling systems from educational and biological to industrial and organisational ones, enable the analysis of static, dynamic and temporal characteristics of the modeled system. The existing GN model, according to the theory of generalized nets, can be modified by dropping or adding places, even entire transitions. This assumes a disruption of the static structure of a GN model and cannot be suitable for situations when similar but essentially different solutions need to be made using the GN model. For this purpose, the possibility of generalized nets to manage the capacities of places in transition have been used in this paper. In order to solve this problem, five most common cases of stereoscopic content production have been defined here: real-time studio production (live programme from the studio), realization of a sports event\textemdashlive, post-production services (processing of other people’s stereoscopic material), subtitling/over synchronization and realization of a film programme\textemdashshowing. For each case of the model usage non-necessary characteristics received by tokens in different places are defined. In accordance with GN methodology places with corresponding characteristics are eliminated for particular use-case by setting capacity function to zero. © 2022, Pleiades Publishing, Ltd.},

keywords = {Multimedia systems; Stereo image processing; Generalized net; Mathematical tools; Modelling systems; Multimedia contents; Net model; Organisational; Side effect; Software intensive systems; Static characteristic; Static structures; Studios},

pubstate = {published},

tppubtype = {article}

}

@article{Avdi\'{c}20203285,

title = {Automated labeling of terms in medical reports in Serbian},

author = {Aldina Avdi\'{c} and Ulfeta Marovac and Dragan Jankovi\'{c}},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096654512\&doi=10.3906%2fELK-2002-9\&partnerID=40\&md5=b1b90c80b11480f73353083d67f53750},

doi = {10.3906/ELK-2002-9},

year  = {2020},

date = {2020-01-01},

journal = {Turkish Journal of Electrical Engineering and Computer Sciences},

volume = {28},

number = {6},

pages = {3285 \textendash 3303},

publisher = {Turkiye Klinikleri},

abstract = {Nowadays, many electronic health reports (EHRs) are stored daily. They consist of the structured part and of an unstructured section written in natural language. Due to the limited time for medical examination, EHRs are short reports which often contain errors and abbreviations. Therefore it is a challenge to process an EHR and extract knowledge from this part of the text for different purposes. This paper compares the results of three proposed methods for automatic labeling of medical terms in unstructured parts of EHRs. All words are categorized as words within the medical domain (symptoms, diagnoses, therapies, anatomy, specialties etc.) and those beyond the medical domain (numbers, places, stop words etc.). The first method is based on dictionaries of medical terms, the second on the training set, and the third on the training set and rules. The results of application of different methodologies to reduce a word to its basic form (pure, prefix, stem) are given for each of the methods. The paper shows that in labeling medical terms, the methods based on medical dictionaries (diagnosis, symptoms, medications etc.) do not produce best results, therefore it is better to use manually annotated part of the data set as a model. A significant number of words (17.36%) in medical reports are abbreviations and errors, so for better results, we should focus on creating rules to solve this problem. Better results are obtained for supervised methods compared to the dictionary-based method (with relative improvement of 42.82%). The inclusion of the algorithm for processing errors and abbreviations increased the results (with a relative improvement of 4.21%) and gave the largest F1 measure (0.9082). The advantage of the proposed method is that the use of rules for processing errors and abbreviations provides good results regardless of how the word is reduced to its basic form. © T\"{U}B\.{I}TAK},

note = {All Open Access, Bronze Open Access},

keywords = {Errors; Automated labeling; Automatic labeling; Electronic health; Medical dictionary; Medical domains; Natural languages; Processing errors; Supervised methods; Diagnosis},

pubstate = {published},

tppubtype = {article}

}

@article{Milenkovic2020,

title = {Extensions and adaptations of existing medical information system in order to reduce social contacts during COVID-19 pandemic},

author = {Aleksandar Milenkovic and Dragan Jankovic and Petar Rajkovic},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086514372\&doi=10.1016%2fj.ijmedinf.2020.104224\&partnerID=40\&md5=a60211cda8768050a4e2fc6e6d5518be},

doi = {10.1016/j.ijmedinf.2020.104224},

year  = {2020},

date = {2020-01-01},

journal = {International Journal of Medical Informatics},

volume = {141},

publisher = {Elsevier Ireland Ltd},

abstract = {Objective: The main objective of this paper is the reduction of the COVID-19 pandemic spread by increasing the degree of social distancing by using and upgrading the existing Medical Information System (MIS). Material and methods: The existing MIS MEDIS.NET, currently used in the largest health center in the Balkans, has been adapted and further developed. Results: During the adaptation of existing MIS MEDIS.NET 4 new and 9 existing modules were developed. A quick questionnaire for the smart triage of patients was also implemented. Discussion: The adapted MIS successfully influenced the reduction of social contacts within the Health Center Nis. The need for the arrival of children and their parents to receive appropriate health certificates for the school enrolment is reduced. The therapy of chronic patients has been prolonged for 6 months via an electronic prescription. An online service for the communication between patients and the chosen physicians is provided. Possible social contacts and exposure to the viral environment of patients are reduced by making appointments in extended slots and at determined physical locations. Patients are notified per SMS or email about the availability of chosen and physician on duty. The social distancing of patients and physicians is also established by sending laboratory analyses per email or SMS. Keeping the central registry for COVID-19 is enabled throughout the country. Conclusion: The smart adaptation of MIS, and its collaboration with other state systems can significantly influence the reduction of social contacts and thus mitigate the consequences of COVID-19 pandemic. © 2020 Elsevier B.V.},

note = {All Open Access, Green Open Access},

keywords = {Betacoronavirus; Child; Communication; Contact Tracing; Coronavirus Infections; Humans; Medical Informatics; Pandemics; Pneumonia},

pubstate = {published},

tppubtype = {article}

}

@article{Savi\'{c}2020251,

title = {Students’ preferences in selection of computer science and informatics studies a comprehensive empirical case study},

author = {Milo\v{s} Savi\'{c} and Mirjana Ivanovi\'{c} and Ivan Lukovi\'{c} and Boris Deliba\v{s}i\'{c} and Jelica Proti\'{c} and Dragan Jankovi\'{c}},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100549175\&doi=10.2298%2fCSIS200901054S\&partnerID=40\&md5=b11242db86b372e10fa6cc5364d6b53b},

doi = {10.2298/CSIS200901054S},

year  = {2020},

date = {2020-01-01},

journal = {Computer Science and Information Systems},

volume = {18},

number = {1},

pages = {251 \textendash 283},

publisher = {ComSIS Consortium},

abstract = {A selection of Computer Science, Informatics or similar study programs for academic studies evidently becomes an emerging choice of a vast number of students in recent years. To address some of the open questions, we performed an empirical study based on a survey, with a goal to find out the main motivating factors directing students to select computer science, informatics or similar programs for studying in a much greater extent. The survey was conducted on a sample of 1517 students from five well established, and most traditional faculties of computer science and informatics at three largest university cities in Serbia: Belgrade, Novi Sad, and Ni\v{s}. The created sample is representative enough to illustrate the current situation and trends common for many similar societies. Our first analysis shows that the main motivating factor to select computer science or informatics study program at all faculties is the students’ motivation to study just that topic, while at management faculty it is significantly less important. However, we also noticed that significant number of students wished to study something else but chose computer science and informatics due to possibility of finding jobs easier and of earning higher salaries in industry. The most important influential factors to choose a computer science or informatics major come from family members, and close relatives. The perceived brand and reputation of a faculty also plays a significant role. Students being examined prevalently tend to be satisfied with the faculty they have chosen. However, many of them see themselves leaving the country in a near or far future. © 2020, ComSIS Consortium. All rights reserved.},

note = {All Open Access, Gold Open Access, Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Jovanovi\'{c}20192817,

title = {Patient comfort level prediction during transport using artificial neural network},

author = {\v{Z}eljko Jovanovi\'{c} and Marija Blagojevi\'{c} and Dragan Jankovi\'{c} and Aleksandar Peuli\'{c}},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072603479\&doi=10.3906%2felk-1807-258\&partnerID=40\&md5=8fc03afac2af1582b44e06345928d8c0},

doi = {10.3906/elk-1807-258},

year  = {2019},

date = {2019-01-01},

journal = {Turkish Journal of Electrical Engineering and Computer Sciences},

volume = {27},

number = {4},

pages = {2817 \textendash 2832},

publisher = {Turkiye Klinikleri},

abstract = {Since patient comfort during transport is a matter of paramount importance, this paper aims to determine the possibilities of applying neural networks for its prediction and monitoring. Specific objectives of the research include monitoring and predicting patient transport comfort, with subjective assessment of comfort by medical personnel. An original Android application that collects signals from an accelerometer and a GPS sensor was used with the aim of achieving the research goals. The collected signals were processed and a total of twelve parameters were calculated. A multilayer perceptron was created in the proposed research. The evaluation results indicate acceptable accuracy and give the possibility to apply the same model to the next patient transport. The root mean square error was 0.0215 and the overall confusion matrix prediction accuracy was 90.07%. Moreover, the results were validated in real usage. The limitations and future work are highlighted. © T\"{U}B\.{I}TAK},

note = {All Open Access, Bronze Open Access},

keywords = {Accelerometers; Android (operating system); Mean square error; Neural networks; Android applications; Confusion matrices; Evaluation results; Medical personnel; Patient comfort; Prediction accuracy; Root mean square errors; Subjective assessments; Forecasting},

pubstate = {published},

tppubtype = {article}

}

@article{Jovanovic201961,

title = {Comfort level classification during patients transport},

author = {Zeljko Jovanovic and Marina Milosevic and Dragan Jankovic and Aleksandar Peulic},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85061066421\&doi=10.3233%2fTHC-181411\&partnerID=40\&md5=c8aec01521ed53f05000d8241c0d2c3d},

doi = {10.3233/THC-181411},

year  = {2019},

date = {2019-01-01},

journal = {Technology and Health Care},

volume = {27},

number = {1},

pages = {61 \textendash 77},

publisher = {IOS Press},

abstract = {BACKGROUND: Passenger comfort is affected by many factors. Patient comfort is even more specific due to its mental and physical health condition. OBJECTIVE: Developing a system for monitoring patient transport conditions with the comfort level classification, which is affected by the patient parameters. METHODS: Smartphone with the developed Android application was installed in an EMS to monitor patient transport between medical institutions. As a result, 10 calculated parameters are generated in addition to the GPS data and the subjective comfort level. Three classifiers are used to classify the transportation. At the end, the adjustment of classified comfort levels is performed based on the patient's medical condition, age and gender. RESULTS: Modified SVM classifier provided the best overall classification results with the precision of 90.8%. Furthermore, a model that represents patient sensitivity to transport vibration, based on the patient's medical condition, is proposed and the final classification results are presented. CONCLUSIONS: The Android application is mobile, simple to install and use. According to the obtained results, SVM and Naive Bayes classifier gave satisfying results while KNN should be avoided. The developed model takes transport comfort and the patient's medical condition into consideration, so it is suitable for the patient transport comfort classification. © 2019 - IOS Press and the authors. All rights reserved},

keywords = {Adolescent; Adult; Age Factors; Bayes Theorem; Child; Child, Preschool; Female; Humans; Infant; Infant},

pubstate = {published},

tppubtype = {article}

}

@article{Milosevic2018729,

title = {Early diagnosis and detection of breast cancer},

author = {Marina Milosevic and Dragan Jankovic and Aleksandar Milenkovic and Dragan Stojanov},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054334418\&doi=10.3233%2fTHC-181277\&partnerID=40\&md5=5f90c3d3523dbb578c665422414cbff2},

doi = {10.3233/THC-181277},

year  = {2018},

date = {2018-01-01},

journal = {Technology and Health Care},

volume = {26},

number = {4},

pages = {729 \textendash 759},

publisher = {IOS Press},

abstract = {BACKGROUND: Breast cancer is the most common malignancy in women. It is often characterized by a lack of early symptoms, which results in late detection of the disease. Detection at advanced stages of the decease implies the treatment is more difficult and uncertain. The appropriate screening programs have been conducted within the organized preventive examinations and have made significant contributions to the early breast cancer detection. OBJECTIVE: It is necessary to improve the screening process in order to reduce the percentage of female population that is not covered by screening programs and increase the number of early-detected breast cancers. The improvement of the screening program may be reflected in the following: more efficient determination of the list of the women who have to undergo preventive examination, introduction of screening program in thermography as a diagnostic method applied in pre-screening stage, more efficient analysis of mammograms and continuous follow up of patients. METHODS: The identification of target population for breast cancer screening program has been based on the age of women. The improvement of the early breast cancer diagnosis process proposed in this paper is reflected in more efficient determination of the group of women who have to undergo preventive examination based on the factors affecting the occurrence of breast cancer. Inclusion of the pre-screening phase in which thermal imaging could be applied and software support to mammographic detection of tumor are suggested. RESULTS: This paper describes the breast cancer, current screening program and techniques for early-stage breast cancer detection, module of medical information system MEDIS.NET for creating screening list based on the analysis of risk factors affecting the occurrence of breast cancer, mammography and role of thermal imaging in the process of early breast cancer detection. It also presents an overview on important achievements in computer-Aided detection and diagnosis of breast cancer in mammography and thermography. CONCLUSIONS: Based on the obtained results, dynamics of preventive examinations for particular groups of women that is different from the standard two-year examinations, can be successfully defined. It can be concluded that the use of a computer system for tumor diagnosis in mammogram based on various methods of image processing can help doctors in decision-making, while the use of thermal imaging in the pre-screening phase would significantly reduce the list of women for screening mammograms. © © 2018-IOS Press and the authors. All rights reserved.},

keywords = {Age Factors; Breast Neoplasms; Comorbidity; Early Detection of Cancer; Genetic Predisposition to Disease; Health Behavior; Humans; Image Interpretation, Computer-Assisted; Mammography; Risk Factors; Sex Factors; Thermography; age; breast tumor; comorbidity; computer assisted diagnosis; early cancer diagnosis; ethnology; genetic predisposition; health behavior; human; mammography; procedures; risk factor; sex factor; thermography},

pubstate = {published},

tppubtype = {article}

}

@article{Rajkovi\'{c}201880,

title = {Checking the potential shift to perceived usefulness\textemdashThe analysis of users’ response to the updated electronic health record core features},

author = {Petar Rajkovi\'{c} and Dejan Aleksi\'{c} and Dragan Jankovi\'{c} and Aleksandar Milenkovi\'{c} and Ivan Petkovi\'{c}},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046360083\&doi=10.1016%2fj.ijmedinf.2018.04.011\&partnerID=40\&md5=0723909d2aead3a7cd640aced45dabff},

doi = {10.1016/j.ijmedinf.2018.04.011},

year  = {2018},

date = {2018-01-01},

journal = {International Journal of Medical Informatics},

volume = {115},

pages = {80 \textendash 91},

publisher = {Elsevier Ireland Ltd},

abstract = {Objective: The primary objective of this paper is to identify the main factors which have an impact on the users’ attitude towards the functionalities representing the perceived ease of use and to those representing the perceived usefulness. Another objective is to examine whether there occurred a shift towards the perceived usefulness of users’ behavior over a period of time. To support these objectives, two different cases are examined \textendash the case in which users are simultaneously offered basic and updated functionalities, and the one in which users are offered a completely new set of features. The results of this study are expected to exert a significant impact on a further development of new software components, as well as the updates of the existing ones. Material and methods: As the starting point, there were employed the user behavior indicators defined in similar researches and conducted in the countries with a similar cultural background or with a comparatively similar national healthcare system. What ensued was an updated set of functionalities offered within the electronic health record based medical information system. Instead of the survey being posted, the effects of implanted updates were measured through the analysis of the collected data. The data collected in the Nis Primary and Ambulatory Care Center during a four-year period represented the material used in the research. The obtained records indicating the usage of the initial and updated visit registration form, as well as the usage of the new types of visits, were examined in relation to the technology acceptance model and integrated behavior model. Results: The response to the initial functionalities, perceived as easy to use, was high as expected since they kept the users in their “comfort zone”. As regards the updated features, the ones corresponding to the perceived usefulness, the initial overall acceptance rate was 60%, while the overall increase of their acceptance was around 20%. The overall usage of the newly introduced features was doubled in some cases throughout the four-year period, while some of them were not accepted as expected. Discussion: Carefully designed additional functionalities, aimed to improve the most common daily activities, have a significant potential to be accepted by the medical professionals. The shift from the perceived ease of use to the perceived usefulness is not uniform, nor is its use in different departments or by the users of the same department. A higher acceptance rate was observed in the departments with more complex administrative procedures, as well as among the users having contacts with more patients and using the system for a longer period. Conclusion: When accepting new features, medical professionals will initially choose the simpler ones with obvious benefits. If the usage of a feature triggers indirect benefits, the number of examined patients is of a crucial importance for the acceptance of that feature. In the event of the advanced functionality with an extended set of options competing with the simple functionality covering basic requirements, the latter will be used. A feature design, together with a proper training, system stability and ensuring utilization, represent a key point for increasing the positive impact that the information system can have in many application areas, including the healthcare. © 2018 Elsevier B.V.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Atanasovski2018915,

title = {On defining a model driven architecture for an enterprise e-health system},

author = {Blagoj Atanasovski and Milos Bogdanovic and Goran Velinov and Leonid Stoimenov and Aleksandar S. Dimovski and Bojana Koteska and Dragan Jankovic and Irena Skrceska and Margita Kon-Popovska and Boro Jakimovski},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053593863\&doi=10.1080%2f17517575.2018.1521996\&partnerID=40\&md5=73b85b43ca077cdf6f057e2f084fc4b2},

doi = {10.1080/17517575.2018.1521996},

year  = {2018},

date = {2018-01-01},

journal = {Enterprise Information Systems},

volume = {12},

number = {8-9},

pages = {915 \textendash 941},

publisher = {Taylor and Francis Ltd.},

abstract = {The national e-health systems implemented in Serbia as ”MojDoktor” (MyDoctor) and in Macedonia as ”MojTermin” (MyAppointment) are based on the same integrated health information platform. Its architecture was designed to allow for process oriented development with agile methodologies. This methodology allowed for fast deployment and adoption, but a change in the architecture to a more formal approach is required to assure its extensibility, soundness, interoperability and standardization. In this paper, we propose a formalization of the system design and its implementation as a Model Driven Architecture®. We develop a set of formal models on several abstraction levels and explain how different layers of the MDA framework are covered using them. We also propose a model for data transformations that will provide interfaces for interoperability between an external and our system. © 2018, © 2018 Informa UK Limited, trading as Taylor \& Francis Group.},

keywords = {Computer architecture; eHealth; Interoperability; Software design; Systems analysis; Abstraction level; Agile Methodologies; Data transformation; e-Health systems; Formal model; Health informations; Integrated information system; Model driven architectures; Software architecture},

pubstate = {published},

tppubtype = {article}

}

@article{Mili\'{c}2018173,

title = {Health care domain mobile reminder for taking prescribed medications},

author = {Eleonora Mili\'{c} and Dragan Jankovi\'{c} and Aleksandar Milenkovi\'{c}},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85031734777\&doi=10.1007%2f978-3-319-68855-8_17\&partnerID=40\&md5=54e174db2dd8251ecbcb17a3b5280984},

doi = {10.1007/978-3-319-68855-8_17},

year  = {2018},

date = {2018-01-01},

journal = {Advances in Intelligent Systems and Computing},

volume = {665},

pages = {173 \textendash 181},

publisher = {Springer Verlag},

abstract = {Nowadays, majority of people as a main problem for their poor health and bad psycho-physical condition states the lack of time. Commitments, dynamic and stressful way of life lead to people being negligent of themselves. Thus, their health condition is damaged. The big problem are acute patients, but also the patients who have a chronic disease and who should take prescribed medications regularly, and who, for some reason, are prevented or have forgotten to take the prescribed dosage of the medicaments. Due to the inadequate taking of the therapy, the time for patient’s recovery is significantly prolonged or the existing problem is not relieved (with chronic patients). PersonalMedicationReminder is an Android application that downloads the prescriptions from the server of a health care institution or allows the user to insert the over-the-counter drugs (without prescription therapy). The application allows patients to create reminders and receive notifications which would inform them about the time for the next receiving of the therapy. The application downloads the prescriptions from the electronic medical record of the patient from the medical information system MEDIS.NET which is used in health institutions for primary health care in Republic of Serbia [1, 2]. The problems that occurred during the application development are also shown in the paper. In the conclusion are stated the directions of the further research and improvement of the mobile application. © Springer International Publishing AG 2018.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Radovic2018394,

title = {OntoCIP - an ontology of comprehensive integrative puzzle assessment method suitable for automatic question generation},

author = {Maja Radovic and Milorad Tosic and Danijela Milosevic and Dragan Jankovic},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042313641\&doi=10.1007%2f978-3-319-73204-6_44\&partnerID=40\&md5=dec2a0b67a36d208f623aecd4e915a4b},

doi = {10.1007/978-3-319-73204-6_44},

year  = {2018},

date = {2018-01-01},

journal = {Advances in Intelligent Systems and Computing},

volume = {716},

pages = {394 \textendash 399},

publisher = {Springer Verlag},

abstract = {Application of the Comprehensive Integrative Puzzle (CIP) assessment method is novel in medical education. Because of its high discriminatory quality, its application in medical education increases. However, creating a CIP question can be very labor intensive and time consuming while a team of experts is needed. On the other hand, Semantic web and ontologies have proven their usefulness in fine-grain knowledge management and reasoning. This paper describes a concrete development of ontology for Comprehensive Integrative Puzzle assessment method, called OntoCIP. This ontology supports automatic question generation that will reduce workload for teachers as well as engage domain experts while keeping feasibility, reliability, and validity of CIP assessment method. Conducted evaluation of OntoCIP shows that it is suitable for the purpose. © 2018, Springer International Publishing AG.},

keywords = {Knowledge management; Medical education; Ontology; Teaching; Comprehensive Integrative Puzzle; Domain experts; Fine grains; ITS applications; Labor intensive; Plutonium compounds},

pubstate = {published},

tppubtype = {article}

}

@article{Aleksi\'{c}2017188,

title = {Data summarization method for chronic disease tracking},

author = {Dejan Aleksi\'{c} and Petar Rajkovi\'{c} and Du\v{s}an Vu\v{c}kovi\'{c} and Dragan Jankovi\'{c} and Aleksandar Milenkovi\'{c}},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018602888\&doi=10.1016%2fj.jbi.2017.04.012\&partnerID=40\&md5=0e171becd9dc6d0bc2812e270015709f},

doi = {10.1016/j.jbi.2017.04.012},

year  = {2017},

date = {2017-01-01},

journal = {Journal of Biomedical Informatics},

volume = {69},

pages = {188 \textendash 202},

publisher = {Academic Press Inc.},

abstract = {Objectives Bearing in mind the rising prevalence of chronic medical conditions, the chronic disease management is one of the key features required by medical information systems used in primary healthcare. Our research group paid a particular attention to this specific area by offering a set of custom data collection forms and reports in order to improve medical professionals’ daily routine. The main idea was to provide an overview of history for chronic diseases, which, as it seems, had not been properly supported in previous administrative workflows. After five years of active use of medical information systems in more than 25 primary healthcare institutions, we were able to identify several scenarios that were often end-user-action dependent and could result in the data related to chronic diagnoses being loosely connected. An additional benefit would be a more effective identification of potentially new patients suffering from chronic diseases. Methods For this particular reason, we introduced an extension of the existing data structures and a summarizing method along with a specific tool that should help in connecting all the data related to a patient and a diagnosis. The summarization method was based on the principle of connecting all of the records pertaining to a specific diagnosis for the selected patient, and it was envisaged to work in both automatic and on-demand mode. The expected results were a more effective identification of new potential patients and a completion of the existing histories of diseases associated with chronic diagnoses. Results The current system usage analysis shows that a small number of doctors used functionalities specially designed for chronic diseases affecting less than 6% of the total population (around 11,500 out of more than 200,000 patients). In initial tests, the on-demand data summarization mode was applied in general practice and 89 out of 155 users identified more than 3000 new patients with a chronic disease over a three-month test period. During the tests, more than 100,000 medical documents were paired up with the existing histories of diseases. Furthermore, a significant number of physicians that accepted the standard history of disease helped with the identification of the additional 22% of the population. Applying the automatic summarization would help identify all patients with at least one record related to the diagnosis usually marked as chronic, but ultimately, this data had to be filtered and medical professionals should have the final say. Depending on the data filter definition, the total percentage of newly discovered patients with a chronic disease is between 35% and 53%, as expected. Conclusions Although the medical practitioner should have the final say about any medical record changes, new, innovative methods which can help in the data summarization are welcome. In addition to being focused on the summarization in relation to the patient, or to the diagnosis, this proposed method and tool can be effectively used when the patient-diagnosis relation is not one-to-one but many-to-many. The proposed summarization principles were tested on a single type of the medical information system, but can easily be applied to other medical software packages, too. Depending on the existing data structure of the target system, as well as identified use cases, it is possible to extend the data and customize the proposed summarization method. © 2017 Elsevier Inc.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Milosevic2017657,

title = {A comparison of methods for three-class mammograms classification},

author = {Marina Milosevic and Zeljko Jovanovic and Dragan Jankovic},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027516508\&doi=10.3233%2fTHC-160805\&partnerID=40\&md5=8eaf3e7442c0eea7688829e69c050f86},

doi = {10.3233/THC-160805},

year  = {2017},

date = {2017-01-01},

journal = {Technology and Health Care},

volume = {25},

number = {4},

pages = {657 \textendash 670},

publisher = {IOS Press},

abstract = {Background: Mammography is considered the gold standard for early breast cancer detection but it is very difficult to interpret mammograms for many reason. Computer aided diagnosis (CAD) is an important development that may help to improve the performance in breast cancer detection. Objective: We present a CAD system based on feature extraction techniques for detecting abnormal patterns in digital mammograms. Methods: Computed features based on gray-level co-occurrence matrices (GLCM) are used to evaluate the effectiveness of textural information possessed by mass regions. A total of 20 texture features are extracted from each mammogram. The ability of feature set in differentiating normal, benign and malign tissue is investigated using a Support Vector Machine (SVM) classifier, Naive Bayes classifier and K-Nearest Neighbor (k-NN) classifier. The efficiency of classification is provided using cross-validation technique. Support Vector Machine was originally designed for binary classification. We constructed a three-class SVM classifier by combining two binary classifiers and then compared his performance with classifiers intended for multi-class classification. To evaluate the classification performance, confusion matrix and Receiver Operating Characteristic (ROC) analysis were performed. Results: Obtained results indicate that SVM classification results are better than the k-NN and Naive Bayes classification results, with accuracy ratio of 65% according to 51.6% and 38.1%, respectively. The unbalanced classification that occurs in all three classification tests is reason for unsatisfactory accuracy. Conclusions: Obtained experimental results indicate that the proposed three-class SVM classifier is more suitable for practical use than the other two methods. © 2017 - IOS Press and the authors. All rights reserved.},

keywords = {Bayes Theorem; Diagnosis},

pubstate = {published},

tppubtype = {article}

}

@article{Aleksic20172145,

title = {Product configurators in SME one-of-a-kind production with the dominant variation of the topology in a hybrid manufacturing cloud},

author = {Dejan S. Aleksic and Dragan S. Jankovic and Petar Rajkovic},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016406475\&doi=10.1007%2fs00170-017-0286-1\&partnerID=40\&md5=0ecd642ed5dfc699ec39069bdc72406a},

doi = {10.1007/s00170-017-0286-1},

year  = {2017},

date = {2017-01-01},

journal = {International Journal of Advanced Manufacturing Technology},

volume = {92},

number = {5-8},

pages = {2145 \textendash 2167},

publisher = {Springer London},

abstract = {The majority of the current product configurators defined for the small or medium-sized enterprise one-of-a-kind production (SME OKP) with the dominant variation of the product by typology are derived from the assemble-to-order (ATO) production configurators. Unfortunately, they do not provide the customers with the possibility to adjust the products to their specific needs and further configuration-related actions through specialized software interfaces are required. On the basis of a detailed 1-year-long customer behavior tracking and analysis, the following key issues of the actual configurators have been defined: a low degree of the product adjustment, the complexity of the process of modeling the adjusted product, the extension of the leading time, a separated process of modeling, and the establishment of the communication channel between the customer and the manufacturer in the real time. The proposed solution is based on integrating the existing configurators into one common software application. It should act mainly as the necessary real-time communication channel between the customer and manufacturer in order to alleviate the effects of the product complex paradox. With this concept, the reduction of the leading time is observed as the additional positive effect. The case study illustrates the basic principles and technology required for the practical realization of the proposed solution for the configuration processes of the products in the SME OKP for the PVC windows manufacturing in the hybrid manufacturing cloud environment. © 2017, Springer-Verlag London.},

keywords = {Application programs; Communication channels (information theory); Sales; Assemble-to-Order (ATO); Configuration process; Medium sized enterprise; One-of-a-kind production; Product complex; Product configurators; Real-time communication; Specialized software; Manufacture},

pubstate = {published},

tppubtype = {article}

}

@article{Milosevic201549,

title = {Comparative analysis of breast cancer detection in mammograms and thermograms},

author = {Marina Milosevic and Dragan Jankovic and Aleksandar Peulic},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925344935\&doi=10.1515%2fbmt-2014-0047\&partnerID=40\&md5=ad9028a1efddb5639a1bb0d373c169b2},

doi = {10.1515/bmt-2014-0047},

year  = {2015},

date = {2015-01-01},

journal = {Biomedizinische Technik},

volume = {60},

number = {1},

pages = {49 \textendash 56},

publisher = {Walter de Gruyter GmbH},

abstract = {In this paper, we present a system based on feature extraction techniques for detecting abnormal patterns in digital mammograms and thermograms. A comparative study of texture-analysis methods is performed for three image groups: mammograms from the Mammographic Image Analysis Society mammographic database; digital mammograms from the local database; and thermography images of the breast. Also, we present a procedure for the automatic separation of the breast region from the mammograms. Computed features based on gray-level co-occurrence matrices are used to evaluate the effectiveness of textural information possessed by mass regions. A total of 20 texture features are extracted from the region of interest. The ability of feature set in differentiating abnormal from normal tissue is investigated using a support vector machine classifier, Naive Bayes classifier and K-Nearest Neighbor classifier. To evaluate the classification performance, five-fold cross-validation method and receiver operating characteristic analysis was performed. © 2015, Walter de Gruyter GmbH. All rights reserved.},

note = {All Open Access, Bronze Open Access},

keywords = {Algorithms; Breast Neoplasms; Female; Humans; Machine Learning; Mammography; Observer Variation; Radiographic Image Interpretation},

pubstate = {published},

tppubtype = {article}

}

@article{Milosevic20141204,

title = {Thermography based breast cancer detection using texture features and minimum variance quantization},

author = {Marina Milosevic and Dragan Jankovic and Aleksandar Peulic},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84919701099\&partnerID=40\&md5=b2f8fc8dcb3cde5f4491f390992c5abe},

year  = {2014},

date = {2014-01-01},

journal = {EXCLI Journal},

volume = {13},

pages = {1204 \textendash 1215},

publisher = {Leibniz Research Centre for Working Environment and Human Factors},

abstract = {In this paper, we present a system based on feature extraction techniques and image segmen-tation techniques for detecting and diagnosing abnormal patterns in breast thermograms. The proposed system consists of three major steps: feature extraction, classification into normal and abnormal pattern and segmentation of abnormal pattern. Computed features based on Gray Level Co-occurrence Matrices (GLCM) are used to evaluate the effectiveness of textur-al information possessed by mass regions. A total of 20 GLCM features are extracted from thermograms. The ability of feature set in differentiating abnormal from normal tissue is in-vestigated using a Support Vector Machine classifier, Naive Bayes classifier and K-Nearest Neighbor classifier. To evaluate the classification performance, five-fold cross validation method and Receiver operating characteristic analysis was performed. The verification results show that the proposed algorithm gives the best classification results using K-Nearest Neigh-bor classifier and a accuracy of 92.5 %. Image segmentation techniques can play an important role to segment and extract suspected hot regions of interests in the breast infrared images. Three image segmentation techniques: minimum variance quantization, dilation of image and erosion of image are discussed. The hottest regions of thermal breast images are extracted and compared to the original images. According to the results, the proposed method has po-tential to extract almost exact shape of tumors. © 2014, Leibniz Research Centre for Working Environment and Human Factors. All rights reserved.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Miji\'{c}20141147,

title = {Using ICT to support alumni data collection in higher education; [Upotreba IKT s ciljem pru\v{z}anja potpore prikupljanju podataka o biv\v{s}im studentima u visokom obrazovanju]},

author = {Danijel Miji\'{c} and Dragan Jankovi\'{c}},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84920917350\&doi=10.15516%2fcje.v16i4.613\&partnerID=40\&md5=fa649ca66ab9ccaa24a845e7a3e1aa82},

doi = {10.15516/cje.v16i4.613},

year  = {2014},

date = {2014-01-01},

journal = {Croatian Journal of Education},

volume = {16},

number = {4},

pages = {1147 \textendash 1172},

publisher = {FACTEACHEREDUCATION},

abstract = {Getting feedback from external stakeholders, especially alumni and employers, is a challenging task for higher education institutions. It is important for many reasons, such as providing information to policy makers, assessing quality of academic programmes, adapting academic programmes to labour market needs, and marketing purposes. Alumni and employer surveys are usually used as methods for collecting data from stakeholders. Research suggests that major problems in data collection are related to efficiency and effectiveness of data collection process. This paper presents a different method of data collection supported by ICT. A specially designed web portal equipped with advanced alumni tracking and communication features was developed and used for alumni data collection. The web portal was evaluated after a period of real operation by analyzing collected data and conducting an online survey. The evaluation results showed that the web portal could be used as effective, efficient, and useful tool for alumni data collection and communication between alumni and higher education institutions. © 2014, FAC TEACHER EDUCATION. All right reserved.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Milosevic2014701,

title = {Segmentation for the enhancement of microcalcifications in digital mammograms},

author = {Marina Milosevic and Dragan Jankovic and Aleksandar Peulic},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84911095838\&doi=10.3233%2fTHC-140841\&partnerID=40\&md5=c3c8c3b5f3d807110fc8c55b2fdf25f2},

doi = {10.3233/THC-140841},

year  = {2014},

date = {2014-01-01},

journal = {Technology and Health Care},

volume = {22},

number = {5},

pages = {701 \textendash 715},

publisher = {IOS Press},

abstract = {Microcalcification clusters appear as groups of small, bright particles with arbitrary shapes on mammographic images. They are the earliest sign of breast carcinomas and their detection is the key for improving breast cancer prognosis. But due to the low contrast of microcalcifications and same properties as noise, it is difficult to detect microcalcification. This work is devoted to developing a system for the detection of microcalcification in digital mammograms. After removing noise from mammogram using the Discrete Wavelet Transformation (DWT), we first selected the region of interest (ROI) in order to demarcate the breast region on a mammogram. Segmenting region of interest represents one of the most important stages of mammogram processing procedure. The proposed segmentation method is based on a filtering using the Sobel filter. This process will identify the significant pixels, that belong to edges of microcalcifications. Microcalcifications were detected by increasing the contrast of the images obtained by applying Sobel operator. In order to confirm the effectiveness of this microcalcification segmentation method, the Support Vector Machine (SVM) and k-Nearest Neighborhood (k-NN) algorithm are employed for the classification task using cross-validation technique. © 2014 - IOS Press and the authors. All rights reserved.},

keywords = {Algorithms; Breast Diseases; Breast Neoplasms; Calcinosis; Female; Humans; Mammography; Radiographic Image Interpretation, Computer-Assisted; Wavelet Analysis; algorithm; Breast Diseases; Breast Neoplasms; calcinosis; computer assisted diagnosis; female; human; mammography; procedures; wavelet analysis},

pubstate = {published},

tppubtype = {article}

}

@article{Rajkovi\'{c}20131429,

title = {Developing and deploying medical information systems for Serbian public healthcare - challenges, lessons learned and guidelines},

author = {Petar Rajkovi\'{c} and Dragan Jankovi\'{c} and Aleksandar Milenkovi\'{c}},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84880074761\&doi=10.2298%2fCSIS120523056R\&partnerID=40\&md5=877ae70741a530a89cf841fd860f108f},

doi = {10.2298/CSIS120523056R},

year  = {2013},

date = {2013-01-01},

journal = {Computer Science and Information Systems},

volume = {10},

number = {3},

pages = {1429 \textendash 1454},

abstract = {This paper presents major challenges and lessons learned during the process of including and adapting modern medical informatics concepts in challenging circumstances of a health care organization in the Republic of Serbia. The processes of choosing the overall software architecture, application development and later software deployment are examined, and the most critical places (slow network, slow workstations, repetitive data entry, wrong data entered, inappropriate and complex GUI, and low IT knowledge of an end-user) are pointed out, and the general solving strategies are defined. The mentioned strategies are joined together as a general approach for maintaining a complete medical information system life-cycle. Eventually, this approach provides shorter training, efficient support during deployment, more comfortable and efficient work, and makes positive impact on adoption process. In a view of this, our main objective is to specify development and deployment guidelines that can be applied for the information systems developed in different developing countries facing similar problems.},

note = {All Open Access, Gold Open Access, Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Spasi\'{c}201378,

title = {Model-driven framework for design and production of low-budget stereoscopic TV content},

author = {Aleksandar Spasi\'{c} and Dragan Jankovi\'{c}},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84875683641\&partnerID=40\&md5=c8272c069cef077f5ca97e2ed19fed90},

year  = {2013},

date = {2013-01-01},

journal = {Journal of Universal Computer Science},

volume = {19},

number = {1},

pages = {78 \textendash 109},

abstract = {Three-dimensional television (3D TV) is expected by many to be the next step in the advancement of television. Due to significant financial exhaustion during the process of transition from analogue to digital production, low-budget broadcasters are not in the position to invest in a new 3D system. This paper proposes one model-driven framework approach to 3D TV production system applicable to and suitable for low-budget broadcasters.The target of the project is to define one of the possible scenarios for applying stereoscopic 3D technologies to low-budget TV production. 3D TV content production chain is described in the first step of the project. 3D TV production workflow is proposed in the second step. This step has two parts: the analyses of the production stages and their integral processes, and the definition of a problem space model which is suitable for low-budget 3D TV production. The preproduction, production and postproduction phases of a low-budget 3D TV production are described during the analyses of 3D TV content production workflow. The UML is used as a modelling tool. The behavioural description of a program production is modelled by the Use Case diagram. A state machine diagram is used to describe the dynamic behavioral representation and the life cycle of a 3D content. The flow and dependencies in 3D workflow are modelled by using the activity diagrams. The structural static representation (domain model) is presented by a class diagram. © J.UCS.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Aleksi\'{c}2012397,

title = {A case study on the object-oriented framework for modeling product families with the dominant variation of the topology in the one-of-a-kind production},

author = {Dejan Slobodan Aleksi\'{c} and Dragan S. Jankovi\'{c} and Leonid V. Stoimenov},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84857784450\&doi=10.1007%2fs00170-011-3466-4\&partnerID=40\&md5=594a09ed171bc6b3f66440271db6be2c},

doi = {10.1007/s00170-011-3466-4},

year  = {2012},

date = {2012-01-01},

journal = {International Journal of Advanced Manufacturing Technology},

volume = {59},

number = {1-4},

pages = {397 \textendash 412},

abstract = {Traditional configuration-based product family modeling techniques do not yield favorable solutions for modeling the product families with the dominant product topology variations. This paper presents the case study for the modeling of variations of the product configuration, parameters, and topologies in mass production of custom windows and doors in a one-of-a-kind production (OKP) company. The case study is based on the object-oriented product family modeling framework we developed for OKP which is characterized by the dominant product variation by topology. The problem of variation in topology in our framework is solved by the manual model transformation in the computer-aided design module which creates a new metamodel of products with the desired topology and which is the basis for a further, automatic model transformation. Usage of our framework has a positive effect on the level of the product customizations and shortening of the leading time which helps OKP companies in obtaining a better position at the market. Our software solution for the designing and manufacturing of custom windows and doors based on our framework is implemented in more than 300 mostly small- and medium-sized enterprises. It proves our concept which can be used for the realization of the information systems for computer-aided one-of-a-kind production in the companies with a different production plan. © 2011 Springer-Verlag London Limited.},

keywords = {Computer aided design; Industry; Production control; Research; Mass customization; Model transformations; Objectoriented modeling; One-of-a-kind production; Product families; UML; Topology},

pubstate = {published},

tppubtype = {article}

}