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Robert Moskovitch - Publications

Affiliations: 
2013-2016 Biomedical Informatics Columbia University, New York, NY 
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31 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2023 Itzhak N, Pessach IM, Moskovitch R. Prediction of acute hypertensive episodes in critically ill patients. Artificial Intelligence in Medicine. 139: 102525. PMID 37100504 DOI: 10.1016/j.artmed.2023.102525  0.315
2022 Novitski P, Cohen CM, Karasik A, Hodik G, Moskovitch R. Temporal patterns selection for All-Cause Mortality prediction in T2D with ANNs. Journal of Biomedical Informatics. 134: 104198. PMID 36100163 DOI: 10.1016/j.jbi.2022.104198  0.379
2022 Novitski P, Cohen CM, Karasik A, Shalev V, Hodik G, Moskovitch R. All-cause mortality prediction in T2D patients with iTirps. Artificial Intelligence in Medicine. 130: 102325. PMID 35809964 DOI: 10.1016/j.artmed.2022.102325  0.33
2020 Mateless R, Rejabek D, Margalit O, Moskovitch R. Decompiled APK based malicious code classification Future Generation Computer Systems. 110: 135-147. DOI: 10.1016/J.Future.2020.03.052  0.319
2019 Moskovitch R, Shahar Y, Wang F, Hripcsak G. Temporal Biomedical Data Analytics. Journal of Biomedical Informatics. PMID 30654029 DOI: 10.1016/J.Jbi.2018.12.006  0.303
2017 Shknevsky A, Shahar Y, Moskovitch R. Consistent Discovery of Frequent Interval-Based Temporal Patterns in Chronic Patients' Data. Journal of Biomedical Informatics. PMID 28987378 DOI: 10.1016/J.Jbi.2017.10.002  0.36
2017 Moskovitch R, Polubriaginof F, Weiss A, Ryan P, Tatonetti N. Procedure Prediction from Symbolic Electronic Health Records via Time Intervals Analytics. Journal of Biomedical Informatics. PMID 28823923 DOI: 10.1016/J.Jbi.2017.07.018  0.653
2017 Nissim N, Shahar Y, Elovici Y, Hripcsak G, Moskovitch R. Inter-labeler and intra-labeler variability of condition severity classification models using active and passive learning methods. Artificial Intelligence in Medicine. PMID 28456512 DOI: 10.1016/J.Artmed.2017.03.003  0.378
2016 Moskovitch R, Choi H, Hripcsak G, Tatonetti N. Prognosis of Clinical Outcomes with Temporal Patterns and Experiences with One Class Feature Selection. Ieee/Acm Transactions On Computational Biology and Bioinformatics / Ieee, Acm. PMID 27429447 DOI: 10.1109/Tcbb.2016.2591539  0.652
2016 Nissim N, Boland MR, Tatonetti NP, Elovici Y, Hripcsak G, Shahar Y, Moskovitch R. Improving Condition Severity Classification with an Efficient Active Learning Based Framework. Journal of Biomedical Informatics. PMID 27016383 DOI: 10.1016/J.Jbi.2016.03.016  0.702
2016 Nissim N, Cohen A, Moskovitch R, Shabtai A, Edri M, BarAd O, Elovici Y. Keeping pace with the creation of new malicious PDF files using an active-learning based detection framework Security Informatics. 5. DOI: 10.1186/S13388-016-0026-3  0.403
2016 Moskovitch R, Walsh C, Wang F, Hripcsak G, Tatonetti N. Outcomes prediction via time intervals related patterns Proceedings - Ieee International Conference On Data Mining, Icdm. 2016: 919-924. DOI: 10.1109/ICDM.2015.143  0.59
2016 Nissim N, Moskovitch R, BarAd O, Rokach L, Elovici Y. ALDROID: efficient update of Android anti-virus software using designated active learning methods Knowledge and Information Systems. 49: 795-833. DOI: 10.1007/S10115-016-0918-Z  0.378
2015 Boland MR, Jacunski A, Lorberbaum T, Romano JD, Moskovitch R, Tatonetti NP. Systems biology approaches for identifying adverse drug reactions and elucidating their underlying biological mechanisms. Wiley Interdisciplinary Reviews. Systems Biology and Medicine. PMID 26559926 DOI: 10.1002/Wsbm.1323  0.414
2015 Nissim N, Boland MR, Moskovitch R, Tatonetti NP, Elovici Y, Shahar Y, Hripcsak G. An active learning framework for efficient condition severity classification Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 9105: 13-24. DOI: 10.1007/978-3-319-19551-3_3  0.685
2014 Nissim N, Moskovitch R, Rokach L, Elovici Y. Novel active learning methods for enhanced PC malware detection in windows OS Expert Systems With Applications. 41: 5843-5857. DOI: 10.1016/J.Eswa.2014.02.053  0.394
2014 Moskovitch R, Shahar Y. Classification-driven temporal discretization of multivariate time series Data Mining and Knowledge Discovery. 29: 871-913. DOI: 10.1007/S10618-014-0380-Z  0.411
2014 Moskovitch R, Shahar Y. Classification of multivariate time series via temporal abstraction and time intervals mining Knowledge and Information Systems. 45: 35-74. DOI: 10.1007/S10115-014-0784-5  0.386
2013 Moskovitch R, Shahar Y. Fast time intervals mining using the transitivity of temporal relations Knowledge and Information Systems. 42: 21-48. DOI: 10.1007/S10115-013-0707-X  0.328
2012 Shabtai A, Moskovitch R, Feher C, Dolev S, Elovici Y. Detecting unknown malicious code by applying classification techniques on OpCode patterns Security Informatics. 1. DOI: 10.1186/2190-8532-1-1  0.325
2012 Feher C, Elovici Y, Moskovitch R, Rokach L, Schclar A. User identity verification via mouse dynamics Information Sciences. 201: 19-36. DOI: 10.1016/J.Ins.2012.02.066  0.311
2012 Nissim N, Moskovitch R, Rokach L, Elovici Y. Detecting unknown computer worm activity via support vector machines and active learning Pattern Analysis and Applications. 15: 459-475. DOI: 10.1007/S10044-012-0296-4  0.349
2010 shabtai A, Potashnik D, Fledel Y, Moskovitch R, Elovici Y. Monitoring, analysis, and filtering system for purifying network traffic of known and unknown malicious content Security and Communication Networks. 4: 947-965. DOI: 10.1002/Sec.229  0.329
2009 Moskovitch R, Shahar Y. Vaidurya: a multiple-ontology, concept-based, context-sensitive clinical-guideline search engine. Journal of Biomedical Informatics. 42: 11-21. PMID 18721900 DOI: 10.1016/J.Jbi.2008.07.003  0.338
2009 Shabtai A, Moskovitch R, Elovici Y, Glezer C. Detection of malicious code by applying machine learning classifiers on static features: A state-of-the-art survey Information Security Technical Report. 14: 16-29. DOI: 10.1016/J.Istr.2009.03.003  0.375
2009 Moskovitch R, Stopel D, Feher C, Nissim N, Japkowicz N, Elovici Y. Unknown malcode detection and the imbalance problem Journal in Computer Virology. 5: 295-308. DOI: 10.1007/S11416-009-0122-8  0.316
2009 Stopel D, Moskovitch R, Boger Z, Shahar Y, Elovici Y. Using artificial neural networks to detect unknown computer worms Neural Computing and Applications. 18: 663-674. DOI: 10.1007/S00521-009-0238-2  0.38
2008 Moskovitch R, Elovici Y, Rokach L. Detection of unknown computer worms based on behavioral classification of the host Computational Statistics & Data Analysis. 52: 4544-4566. DOI: 10.1016/J.Csda.2008.01.028  0.376
2008 Kuflik T, Pertot I, Moskovitch R, Zasso R, Pellegrini E, Gessler C. Optimization of Fire blight scouting with a decision support system based on infection risk Computers and Electronics in Agriculture. 62: 118-127. DOI: 10.1016/J.Compag.2007.12.003  0.338
2006 Moskovitch R, Cohen-Kashi S, Dror U, Levy I, Maimon A, Shahar Y. Multiple hierarchical classification of free-text clinical guidelines. Artificial Intelligence in Medicine. 37: 177-90. PMID 16730962 DOI: 10.1016/J.Artmed.2006.04.001  0.397
2004 Shahar Y, Young O, Shalom E, Galperin M, Mayaffit A, Moskovitch R, Hessing A. A framework for a distributed, hybrid, multiple-ontology clinical-guideline library, and automated guideline-support tools. Journal of Biomedical Informatics. 37: 325-44. PMID 15488747 DOI: 10.1016/J.Jbi.2004.07.001  0.341
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