Advancing healthcare through technology

Call between 8 a.m. and 4 p.m.

(+381) 63448872

Mail us for support

medlab@elfak.ni.ac.rs

Laboratory address

Aleksandra Medvedeva 4

Niš, Serbia

References

Our publications

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 Algorithms; Boolean functions; Computational complexity; Decision theory; Graph theory; Many valued logics; Theorem proving; Binary decision diagrams; Discrete logic functions; Lower bound sifting; Multiple valued decision diagrams; Multiple valued logic functions; Data structures Algorithms; Boolean functions; Computational complexity; Logic programming; Software engineering; Dual polarity routes; Fixed-polarity Galois field (FPGF); Logic design Algorithms; Breast Neoplasms; Female; Humans; Machine Learning; Mammography; Observer Variation; Radiographic Image Interpretation Algorithms; Computational complexity; Decision theory; Logic design; Mathematical transformations; Recursive functions; Signal processing; Spectrum analysis; Binary decision diagram method; Logic synthesis; Orthogonal transform; Walsh transform; Binary sequences Artificial intelligence; Population statistics; Efficient implementation; Health systems; Hypercube; Screening programs; Software modules; Software support; Diagnosis Automatic notification; Health centers; ITS applications; Medical informatics; Module integration; Notification systems; Republic of Serbia; System response; Medical information systems Bayes Theorem; Diagnosis Binary decision diagrams; Broadcasting; Cables; Decision theory; Decision diagram; Discrete functions; Switching functions Bioinformatics; Database systems; Internet; Management information systems; Centralized architecture; Centralized systems; Database replication; Distributed database; distributed DBMS; Internet connection; Medical information system; Platform independent; replication conflicts; Information systems Bioinformatics; Diseases; Hospital data processing; Information use; Patient treatment; Search engines; Collaboration; Condition; Distribution; Health care professionals; Health data; Health monitoring; Healthcare institutions; IS; Patient data; Republic of Serbia; Medical information systems Bioinformatics; E-learning; Health; Health risks; Information systems; Complex task; data suggestion system; Domain-specific knowledge; General practitioners; Health information systems; Medical practitioner; Potential errors; System acceptance; Medical information systems Bioinformatics; Health; Health care; Information systems; Records management; Data reporting; Electronic health record; Health care information system; Medical information system; Medical research; OLAP in healthcare; Medical computing Classification (of information); Medical imaging; Remote sensing; Semantic Segmentation; Semantics; Context-Aware; Feature; Flood plains; Region segmentation; Remote-sensing; Semantic image segmentations; Shallow classifier; Super pixels; Supervised classifiers; Superpixels Computational complexity; Decision theory; Fast Fourier transforms; Logic design; Spectrum analysis; Switching functions; Decision diagrams (DD); Spectral transforms (ST); Formal logic Computational complexity; Integrated circuit layout; Spectrum analysis; Transfer functions; VLSI circuits; Wavelet transforms; Circuit synthesis complexity; Fast Haar transform; Fast Walsh transform; Haar wavelet series; Electric network analysis Computational complexity; Mathematical models; Optimization; Polynomials; Switching functions; Fixed polarity polynomial expressions; Multiple valued logic functions; Many valued logics Computational methods; Computer software; Mathematical models; Tracking (position); NAVSTAR; Satellite tracking; Visual observing methods; Satellite communication systems 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 Data reduction; Diagnosis; Information science; Information technology; Patient treatment; Research; Societies and institutions; User interfaces; Web services; Collaborative IT platform; Electronic healthcare records; Medical data analysis; OLAP; Rare disease; Diseases Deep neural networks; Semantic Segmentation; Convolutional neural network; Explainability; Explainable artificial intelligence (XAI); Grad-CAM; Image data; Images classification; Interpretability; Neural network architecture; Semantic objects; Semantic segmentation; Convolutional neural networks Diagnosis; Patient treatment; Collaboration; Edoktor; EHR; General practitioners; MEDIS.; NET; Patient state; Recommended therapy; Republic of Serbia; Software-systems; Medical information systems Electronic mail; Electronics packaging; Flow visualization; Health; Information use; Laboratories; Nickel; Servers; XML; Dynamic reports; Health services; Healthcare facility; Intelligence tool; Software modules; Medical information systems Errors; Automated labeling; Automatic labeling; Electronic health; Medical dictionary; Medical domains; Natural languages; Processing errors; Supervised methods; Diagnosis Internet; Medical information systems; Centralized systems; Database replication; Distributed DBMS; Healthcare facility; Internet connection; Platform independent; Replication conflicts; Threelayer architecture; Database systems Knowledge management; Medical education; Ontology; Teaching; Comprehensive Integrative Puzzle; Domain experts; Fine grains; ITS applications; Labor intensive; Plutonium compounds Medical information systems; Radiation; Scheduling; Telephone systems; Diagnostic imaging; DICOM format; Electronic health record; Health centers; Integral part; Medical images; Primary healthcare; Republic of Serbia; Short text messages; Software modules; Software support; Radiology Number theory; Polynomials; Four valued logic functions; Galois field representations; Reed Muller Fourier representations; Formal logic Preschool; Female; Humans; Infant; Infant

2013

1.

Milenkovic, Aleksandar M.; Markovic, Ivica M.; Jankovic, Dragan S.; Rajkovic, Petar J.

Using of Raspberry Pi for data acquisition from biochemical analyzers Conference

vol. 2, 2013.

Abstract | Links | BibTeX | Tags: Cables; Data acquisition; Medical information systems; analyzer; Automatic data acquisition; Biochemical laboratories; Electronic health record; Laboratory information system; Medical laboratories; MEDIS.NET; Mono Framework; Laboratories

@conference{Milenkovic2013389,

title = {Using of Raspberry Pi for data acquisition from biochemical analyzers},

author = {Aleksandar M. Milenkovic and Ivica M. Markovic and Dragan S. Jankovic and Petar J. Rajkovic},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84893631637\&doi=10.1109%2fTELSKS.2013.6704405\&partnerID=40\&md5=b6bf97ee683dc0545ed683bc5668af46},

doi = {10.1109/TELSKS.2013.6704405},

year  = {2013},

date = {2013-01-01},

journal = {2013 11th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services, TELSIKS 2013},

volume = {2},

pages = {389 \textendash 392},

abstract = {A large number of analyses performed in a biochemical laboratory requires that results of these analyses are automatically acquired from analyzers which can be of different types and produced by various producers. Automatic data acquisition prevents errors which are possible if results are manually transcribed into reports for patients. Beside this, acquired results are saved in database from where they are available to be used in electronic health record (EHR). Above requirement resulted in development of a solution for data acquisition from heterogeneous laboratory analyzers. Here we present the solution which is based on minicomputer Raspberry Pi model B, Raspbian OS, Mono Framework and a.NET Framework 4.0 console application written in C# programming language. Proposed solution is tightly connected with medical information system MEDIS.NET and with laboratory information system LabIS. In order to test whole concept we developed a laboratory simulator which completely implements protocol for biochemical analyzers. The emphasis is on an inexpensive solution which connects a large number of heterogeneous analyzers at a biochemical laboratory. © 2013 IEEE.},

keywords = {Cables; Data acquisition; Medical information systems; analyzer; Automatic data acquisition; Biochemical laboratories; Electronic health record; Laboratory information system; Medical laboratories; MEDIS.NET; Mono Framework; Laboratories},

pubstate = {published},

tppubtype = {conference}

}