The function of introns M Chorev, L Carmel Frontiers in genetics 3, 55, 2012 | 429 | 2012 |
Predicting breast cancer by applying deep learning to linked health records and mammograms A Akselrod-Ballin, M Chorev, Y Shoshan, A Spiro, A Hazan, R Melamed, ... Radiology 292 (2), 331-342, 2019 | 185 | 2019 |
Identification of introns harboring functional sequence elements through positional conservation M Chorev, A Joseph Bekker, J Goldberger, L Carmel Scientific Reports 7 (1), 4201, 2017 | 23 | 2017 |
Computational identification of functional introns: high positional conservation of introns that harbor RNA genes M Chorev, L Carmel Nucleic acids research 41 (11), 5604-5613, 2013 | 23 | 2013 |
JuncDB: an exon–exon junction database M Chorev, L Guy, L Carmel Nucleic acids research 44 (D1), D101-D109, 2016 | 10 | 2016 |
LEMONS–a tool for the identification of splice junctions in transcriptomes of organisms lacking reference genomes L Levin, D Bar-Yaacov, A Bouskila, M Chorev, L Carmel, D Mishmar PloS one 10 (11), e0143329, 2015 | 10 | 2015 |
The function of introns. Front Genet 3: 55 M Chorev, L Carmel | 10 | 2012 |
The function of introns. Front Genet. 2012; 3: 55 M Chorev, L Carmel | 9 | 2012 |
The case of missed cancers: applying AI as a radiologist’s safety net M Chorev, Y Shoshan, A Akselrod-Ballin, A Spiro, S Naor, A Hazan, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 8 | 2020 |
Systems and methods for predicting likelihood of malignancy in a target tissue A Akselrod-Ballin, M Chorev, A Hazan, R Melamed, Y Shoshan, A Spiro US Patent App. 16/442,510, 2020 | 3 | 2020 |
A multi-modal AI-driven cohort selection tool to predict suboptimal non-responders to aflibercept loading-phase for neovascular age-related macular degeneration: PRECISE Study … M Chorev, J Haderlein, S Chandra, G Menon, BJL Burton, I Pearce, ... Journal of Clinical Medicine 12 (8), 3013, 2023 | 2 | 2023 |
Leveraging comprehensive health records for breast cancer risk prediction: A binational assessment M Chorev, V Barros, A Spiro, E Evron, E Barkan, O Kagan, M Amit, ... AMIA Annual Symposium Proceedings 2022, 385, 2022 | 2 | 2022 |
A data-driven decision-support tool for population health policies M Chorev, L Shpigelman, P Bak, A Yaeli, E Michael, Y Goldschmidt MEDINFO 2017: Precision Healthcare through Informatics, 332-336, 2017 | 2 | 2017 |
Comparing the efficacy of anti-seizure medications using matched cohorts on a large insurance claims database L Ness, L Szlak, F Benninger, S Ravid, M Chorev, M Rosen-Zvi, ... Epilepsy Research 201, 107313, 2024 | 1 | 2024 |
A deep neural network witharestricted noisy channel for identification of functional introns AJ Bekker, M Chorev, L Carmel, J Goldberger 2017 IEEE 27th International Workshop on Machine Learning for Signal …, 2017 | 1 | 2017 |
A multi-modal AI-driven cohort selection tool based on response to loading-phase aflibercept for neovascular age-related macular degeneration: PRECISE study M Chorev, J Haderlein, S Chandra, G Menon, B Burton, I Pearce, ... | | 2022 |
Trends in clinical characteristics and associations of severe non-respiratory events related to SARS-CoV-2 T El-Hay, E Karavani, A Peretz, M Ninio, S Ravid, M Chorev, M Rosen-Zvi, ... medRxiv, 2021.03. 24.21251900, 2021 | | 2021 |
Correction to: The Case of Missed Cancers: Applying AI as a Radiologist’s Safety Net M Chorev, Y Shoshan, A Akselrod-Ballin, A Spiro, S Naor, A Hazan, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | | 2020 |
A Predictive Tool For Characterizing And Visualizing Populations Under Counterfactual Treatment Assignment M Chorev, M Amit, P Bak, A Yaeli, T El-Hay, Y Goldschmidt Value in Health 20 (9), A757-A758, 2017 | | 2017 |
Epidemiological Models Lacking Process Noise Can Be Overconfident L Shpigelman, M Chorev, Z Waks, Y Goldschmidt, E Michael Informatics for Health: Connected Citizen-Led Wellness and Population Health …, 2017 | | 2017 |