DEGEL: A Hybrid, Multiple-Ontology Framework for Specification and Retrieval of Clinical Guidelines. - Yuval Shahar; Ohad Young; Erez Shalom; Alon Mayaffit; Robert Moskovitch; Alon Hessing; Maya Galperin (AIME, 2003)

A Multiple-Ontology Customizable Search Interface for Retrieval of Clinical Guidelines. - Robert Moskovitch; Yuval Shahar (CGP, 2004)

The Digital Electronic Guideline Library (DeGeL): A Hybrid Framework for Representation and Use of Clinical Guidelines. - Yuval Shahar; Ohad Young; Erez Shalom; Alon Mayaffit; Robert Moskovitch; Alon Hessing; Maya Galperin (CGP, 2004)

Vaidurya - A Concept-Based, Context-Sensitive Search Engine For Clinical Guidelines. - Robert Moskovitch; Alon Hessing; Yuval Shahar (MedInfo, 2004)

A framework for a distributed, hybrid, multiple-ontology clinical-guideline library, and automated guideline-support tools. - Yuval Shahar; Ohad Young; Erez Shalom; Maya Galperin; Alon Mayaffit; Robert Moskovitch; Alon Hessing (J. Biomed. Informatics, 2004)

Helping Physicians to Organize Guidelines Within Conceptual Hierarchies. - Diego Sona; Paolo Avesani; Robert Moskovitch (AIME, 2005)

Application of Artificial Neural Networks Techniques to Computer Worm Detection. - Dima Stopel; Zvi Boger; Robert Moskovitch; Yuval Shahar; Yuval Elovici (IJCNN, 2006)

Multiple hierarchical classification of free-text clinical guidelines. - Robert Moskovitch; Shiva Cohen-Kashi; Uzi Dror; Iftah Levy; Amit Maimon; Yuval Shahar (Artif. Intell. Medicine, 2006)

Detection of Unknown Computer Worms Activity Based on Computer Behavior using Data Mining. - Robert Moskovitch; Ido Gus; Shay Pluderman; Dima Stopel; Clint Feher; Chanan Glezer; Yuval Shahar; Yuval Elovici (CIDM, 2007)

Detection of Unknown Computer Worms Activity Based on Computer Behavior using Data Mining. - Robert Moskovitch; Ido Gus; Shay Pluderman; Dima Stopel; Chanan Glezer; Yuval Shahar; Yuval Elovici (CISDA, 2007)

Malicious Code Detection and Acquisition Using Active Learning. - Robert Moskovitch; Nir Nissim; Yuval Elovici (ISI, 2007)

Host Based Intrusion Detection using Machine Learning. - Robert Moskovitch; Shay Pluderman; Ido Gus; Dima Stopel; Clint Feher; Yisrael Parmet; Yuval Shahar; Yuval Elovici (ISI, 2007)

Applying Machine Learning Techniques for Detection of Malicious Code in Network Traffic. - Yuval Elovici; Asaf Shabtai; Robert Moskovitch; Gil Tahan; Chanan Glezer (KI, 2007)

Improving the Detection of Unknown Computer Worms Activity Using Active Learning. - Robert Moskovitch; Nir Nissim; Dima Stopel; Clint Feher; Roman Englert; Yuval Elovici (KI, 2007)

Experiments with Hierarchical Concept-Based Search. - Robert Moskovitch; Roee Sa'adon; Eytan Behiri; Susana B. Martins; Aviram Weiss; Yuval Shahar (MedInfo, 2007)

Application of Information Technology: A Comparative Evaluation of Full-text, Concept-based, and Context-sensitive Search. - Robert Moskovitch; Susana B. Martins; Eytan Behiri; Aviram Weiss; Yuval Shahar (J. Am. Medical Informatics Assoc., 2007)

Unknown Malcode Detection Using OPCODE Representation. - Robert Moskovitch; Clint Feher; Nir Tzachar; Eugene Berger; Marina Gitelman; Shlomi Dolev; Yuval Elovici (EuroISI, 2008)

Active learning to improve the detection of unknown computer worms activity. - Robert Moskovitch; Nir Nissim; Roman Englert; Yuval Elovici (FUSION, 2008)

Unknown malcode detection - A chronological evaluation. - Robert Moskovitch; Clint Feher; Yuval Elovici (ISI, 2008)

Unknown malcode detection via text categorization and the imbalance problem. - Robert Moskovitch; Dima Stopel; Clint Feher; Nir Nissim; Yuval Elovici (ISI, 2008)

Malicious Code Detection Using Active Learning. - Robert Moskovitch; Nir Nissim; Yuval Elovici (PinKDD, 2008)

Detection of unknown computer worms based on behavioral classification of the host. - Robert Moskovitch; Yuval Elovici; Lior Rokach (Comput. Stat. Data Anal., 2008)

Medical Temporal-Knowledge Discovery via Temporal Abstraction. - Robert Moskovitch; Yuval Shahar (AMIA, 2009)

Identity theft, computers and behavioral biometrics. - Robert Moskovitch; Clint Feher; Arik Messerman; Niklas Kirschnick; Tarik Mustafic; Seyit Ahmet Çamtepe; Bernhard Löhlein; Ulrich Heister; Sebastian Möller 001; Lior Rokach; Yuval Elovici (ISI, 2009)

A Chronological Evaluation of Unknown Malcode Detection. - Robert Moskovitch; Clint Feher; Yuval Elovici (PAISI, 2009)

Detection of malicious code by applying machine learning classifiers on static features: A state-of-the-art survey. - Asaf Shabtai; Robert Moskovitch; Yuval Elovici; Chanan Glezer (Inf. Secur. Tech. Rep., 2009)

Vaidurya: A multiple-ontology, concept-based, context-sensitive clinical-guideline search engine. - Robert Moskovitch; Yuval Shahar (J. Biomed. Informatics, 2009)

Using artificial neural networks to detect unknown computer worms. - Dima Stopel; Robert Moskovitch; Zvi Boger; Yuval Shahar; Yuval Elovici (Neural Comput. Appl., 2009)

Unknown malcode detection and the imbalance problem. - Robert Moskovitch; Dima Stopel; Clint Feher; Nir Nissim; Nathalie Japkowicz; Yuval Elovici (J. Comput. Virol., 2009)

Continuous Verification Using Keystroke Dynamics. - Tomer Shimshon; Robert Moskovitch; Lior Rokach; Yuval Elovici (CIS, 2010)

Monitoring, analysis, and filtering system for purifying network traffic of known and unknown malicious content. - Asaf Shabtai; Dennis Potashnik; Yuval Fledel; Robert Moskovitch; Yuval Elovici (Secur. Commun. Networks, 2011)

User identity verification via mouse dynamics. - Clint Feher; Yuval Elovici; Robert Moskovitch; Lior Rokach; Alon Schclar (Inf. Sci., 2012)

Detecting unknown computer worm activity via support vector machines and active learning. - Nir Nissim; Robert Moskovitch; Lior Rokach; Yuval Elovici (Pattern Anal. Appl., 2012)

Detecting unknown malicious code by applying classification techniques on OpCode patterns. - Asaf Shabtai; Robert Moskovitch; Clint Feher; Shlomi Dolev; Yuval Elovici (Secur. Informatics, 2012)

ALPD: Active Learning Framework for Enhancing the Detection of Malicious PDF Files. - Nir Nissim; Aviad Cohen 002; Robert Moskovitch; Asaf Shabtai; Mattan Edry; Oren Bar-Ad; Yuval Elovici (JISIC, 2014)

Novel active learning methods for enhanced PC malware detection in windows OS. - Nir Nissim; Robert Moskovitch; Lior Rokach; Yuval Elovici (Expert Syst. Appl., 2014)

An Active Learning Framework for Efficient Condition Severity Classification. - Nir Nissim; Mary Regina Boland; Robert Moskovitch; Nicholas P. Tatonetti; Yuval Elovici; Yuval Shahar; George Hripcsak (AIME, 2015)

Outcomes Prediction via Time Intervals Related Patterns. - Robert Moskovitch; Colin G. Walsh; Fei Wang 001; George Hripcsak; Nicholas P. Tatonetti (ICDM, 2015)

Classification-driven temporal discretization of multivariate time series. - Robert Moskovitch; Yuval Shahar (Data Min. Knowl. Discov., 2015)

Fast time intervals mining using the transitivity of temporal relations. - Robert Moskovitch; Yuval Shahar (Knowl. Inf. Syst., 2015)

Classification of multivariate time series via temporal abstraction and time intervals mining. - Robert Moskovitch; Yuval Shahar (Knowl. Inf. Syst., 2015)

Temporal data analytics. - Robert Moskovitch; Fei Wang 001; Yuval Shahar; George Hripcsak (J. Biomed. Informatics, 2016)

Improving condition severity classification with an efficient active learning based framework. - Nir Nissim; Mary Regina Boland; Nicholas P. Tatonetti; Yuval Elovici; George Hripcsak; Yuval Shahar; Robert Moskovitch (J. Biomed. Informatics, 2016)

ALDROID: efficient update of Android anti-virus software using designated active learning methods. - Nir Nissim; Robert Moskovitch; Oren Bar-Ad; Lior Rokach; Yuval Elovici (Knowl. Inf. Syst., 2016)

Keeping pace with the creation of new malicious PDF files using an active-learning based detection framework. - Nir Nissim; Aviad Cohen 002; Robert Moskovitch; Asaf Shabtai; Matan Edri; Oren Bar-Ad; Yuval Elovici (Secur. Informatics, 2016)

Inter-labeler and intra-labeler variability of condition severity classification models using active and passive learning methods. - Nir Nissim; Yuval Shahar; Yuval Elovici; George Hripcsak; Robert Moskovitch (Artif. Intell. Medicine, 2017)

JASIST special issue on biomedical information retrieval. - Robert Moskovitch; Fei Wang 001; Jian Pei 001; Carol Friedman (J. Assoc. Inf. Sci. Technol., 2017)

Procedure prediction from symbolic Electronic Health Records via time intervals analytics. - Robert Moskovitch; Fernanda Polubriaginof; Aviram Weiss; Patrick B. Ryan; Nicholas P. Tatonetti (J. Biomed. Informatics, 2017)

Consistent discovery of frequent interval-based temporal patterns in chronic patients' data. - Alexander Shknevsky; Yuval Shahar; Robert Moskovitch (J. Biomed. Informatics, 2017)

Prognosis of Clinical Outcomes with Temporal Patterns and Experiences with One Class Feature Selection. - Robert Moskovitch; Hyunmi Choi; George Hripcsak; Nicholas P. Tatonetti (IEEE ACM Trans. Comput. Biol. Bioinform., 2017)

Temporal Pattern-Based Malicious Activity Detection in SCADA Systems (Brief Announcement). - Meir Kalech; Amit Shlomo; Robert Moskovitch (CSCML, 2019)

Temporal biomedical data analytics. - Robert Moskovitch; Yuval Shahar; Fei Wang 001; George Hripcsak (J. Biomed. Informatics, 2019)

Falls Prediction in Care Homes Using Mobile App Data Collection. - Ofir Dvir; Paul Wolfson; Laurence B. Lovat; Robert Moskovitch (AIME, 2020)

Acute Hypertensive Episodes Prediction. - Nevo Itzhak; Aditya Nagori; Edo Lior; Maya Schvetz; Rakesh Lodha; Tavpritesh Sethi; Robert Moskovitch (AIME, 2020)

All-Cause Mortality Prediction in T2D Patients. - Pavel Novitski; Cheli Melzer Cohen; Avraham Karasik; Varda Shalev; Gabriel Hodik; Robert Moskovitch (AIME, 2020)

Decompiled APK based malicious code classification. - Roni Mateless; Daniel Rejabek; Oded Margalit; Robert Moskovitch (Future Gener. Comput. Syst., 2020)

Complete Closed Time Intervals-Related Patterns Mining. - Omer David Harel; Robert Moskovitch (AAAI, 2021)

Temporal pattern-based malicious activity detection in SCADA systems. - Amit Shlomo; Meir Kalech; Robert Moskovitch (Comput. Secur., 2021)

Pkg2Vec: Hierarchical package embedding for code authorship attribution. - Roni Mateless; Oren Tsur; Robert Moskovitch (Future Gener. Comput. Syst., 2021)

Outcomes prediction in longitudinal data: Study designs evaluation, use case in ICU acquired sepsis. - Maya Schvetz; Lior Fuchs; Victor Novack; Robert Moskovitch (J. Biomed. Informatics, 2021)

THAAD: Efficient matching queries under temporal abstraction for anomaly detection. - Roni Mateless; Michael Segal 001; Robert Moskovitch (Perform. Evaluation, 2021)

IPvest: Clustering the IP Traffic of Network Entities Hidden Behind a Single IP Address Using Machine Learning. - Roni Mateless; Haim Zlatokrilov; Liran Orevi; Michael Segal 001; Robert Moskovitch (IEEE Trans. Netw. Serv. Manag., 2021)

Classification of Univariate Time Series via Temporal Abstraction and Deep Learning. - Nevo Itzhak; Shahar Tal; Hadas Cohen; Osher Daniel; Roze Kopylov; Robert Moskovitch (IEEE Big Data, 2022)

All-cause mortality prediction in T2D patients with iTirps. - Pavel Novitski; Cheli Melzer Cohen; Avraham Karasik; Varda Shalev; Gabriel Hodik; Robert Moskovitch (Artif. Intell. Medicine, 2022)

Temporal patterns selection for All-Cause Mortality prediction in T2D with ANNs. - Pavel Novitski; Cheli Melzer Cohen; Avraham Karasik; Gabriel Hodik; Robert Moskovitch (J. Biomed. Informatics, 2022)

Visualization of frequent temporal patterns in single or two populations. - Guy Shitrit; Noam Tractinsky; Robert Moskovitch (J. Biomed. Informatics, 2022)

Multivariate temporal data analysis - a review. - Robert Moskovitch (WIREs Data Mining Knowl. Discov., 2022)

Continuously Predicting the Completion of a Time Intervals Related Pattern. - Nevo Itzhak; Szymon Jaroszewicz; Robert Moskovitch (PAKDD (1), 2023)

The Semantic Adjacency Criterion in Time Intervals Mining. - Alexander Shknevsky; Yuval Shahar; Robert Moskovitch (Big Data Cogn. Comput., 2023)

INSTINCT: Inception-based Symbolic Time Intervals series classification. - Omer David Harel; Robert Moskovitch (Inf. Sci., 2023)

Introduction to the Special Track on Artificial Intelligence and COVID-19. - Martin Michalowski; Robert Moskovitch; Nitesh V. Chawla (J. Artif. Intell. Res., 2023)

Prediction of acute hypertensive episodes in critically ill patients. - Nevo Itzhak; Itai M. Pessach; Robert Moskovitch (Artif. Intell. Medicine, 2023)

TIRPClo: efficient and complete mining of time intervals-related patterns. - Omer David Harel; Robert Moskovitch (Data Min. Knowl. Discov., 2023)

Predictive temporal patterns discovery. - Nofar Sarafian Ben Ari; Robert Moskovitch (Expert Syst. Appl., 2023)

Continuous prediction of a time intervals-related pattern's completion. - Nevo Itzhak; Szymon Jaroszewicz; Robert Moskovitch (Knowl. Inf. Syst., 2023)

Introduction to the Special Track on Artificial Intelligence and COVID-19 (Abstract Reprint). - Martin Michalowski; Robert Moskovitch; Nitesh V. Chawla (AAAI, 2024)

The Velodrome - ProCyclists Data Analytics. - Robert Moskovitch; Perry Sinai; Denis Rize; Liam Holohan; Paulo Saldanha (ISACE, 2024)

Early Multiple Temporal Patterns Based Event Prediction in Heterogeneous Multivariate Temporal Data. - Nevo Itzhak; Szymon Jaroszewicz; Robert Moskovitch (SDM, 2024)

Event prediction by estimating continuously the completion of a single temporal pattern's instances. - Nevo Itzhak; Szymon Jaroszewicz; Robert Moskovitch (J. Biomed. Informatics, 2024)

Sleep apnea test prediction based on Electronic Health Records. - Lama Abu Tahoun; Amit Shay Green; Tal Patalon; Yaron Dagan; Robert Moskovitch (J. Biomed. Informatics, 2024)

Temporal ensemble of multiple patterns' instances for continuous prediction of events. - Nevo Itzhak; Szymon Jaroszewicz; Robert Moskovitch (Mach. Learn., 2025)

Time-intervals-related pattern selection for continuous event prediction. - Nevo Itzhak; Szymon Jaroszewicz; Robert Moskovitch (Pattern Recognit., 2025)

STORM: A MapReduce Framework for Symbolic Time Intervals Series Classification. - Omer David Harel; Robert Moskovitch (ACM Trans. Knowl. Discov. Data, 2025)

Visualization of Professional Cyclists Analytics. - Denis Rize; Perry Sinai; Liam Holohan; Paulo Saldanha; Robert Moskovitch (SN Comput. Sci., 2025)