| Prevalence and impact of myocardial injury in patients hospitalized with COVID-19 infection A Lala, KW Johnson, JL Januzzi, AJ Russak, I Paranjpe, F Richter, S Zhao, ... Journal of the American college of cardiology 76 (5), 533-546, 2020 | 819 | 2020 |
| Immune complement and coagulation dysfunction in adverse outcomes of SARS-CoV-2 infection V Ramlall, PM Thangaraj, C Meydan, J Foox, D Butler, J Kim, B May, ... Nature medicine 26 (10), 1609-1615, 2020 | 292 | 2020 |
| Deep learning and the electrocardiogram: review of the current state-of-the-art S Somani, AJ Russak, F Richter, S Zhao, A Vaid, F Chaudhry, ... EP Europace 23 (8), 1179-1191, 2021 | 190 | 2021 |
| Coronavirus 2019 and people living with human immunodeficiency virus: outcomes for hospitalized patients in New York City K Sigel, T Swartz, E Golden, I Paranjpe, S Somani, F Richter, ... Clinical infectious diseases 71 (11), 2933-2938, 2020 | 184 | 2020 |
| Machine learning to predict mortality and critical events in a cohort of patients with COVID-19 in New York City: model development and validation A Vaid, S Somani, AJ Russak, JK De Freitas, FF Chaudhry, I Paranjpe, ... Journal of medical Internet research 22 (11), e24018, 2020 | 183 | 2020 |
| Federated learning of electronic health records to improve mortality prediction in hospitalized patients with COVID-19: machine learning approach A Vaid, SK Jaladanki, J Xu, S Teng, A Kumar, S Lee, S Somani, ... JMIR medical informatics 9 (1), e24207, 2021 | 140 | 2021 |
| Characterization of patients who return to hospital following discharge from hospitalization for COVID-19 SS Somani, F Richter, V Fuster, JK De Freitas, N Naik, K Sigel, ... Journal of general internal medicine 35, 2838-2844, 2020 | 139 | 2020 |
| Clinical characteristics of hospitalized Covid-19 patients in New York City I Paranjpe, AJ Russak, JK De Freitas, A Lala, R Miotto, A Vaid, ... MedRxiv, 2020.04. 19.20062117, 2020 | 127 | 2020 |
| Covid-19 and people with HIV infection: outcomes for hospitalized patients in New York City K Sigel, T Swartz, E Golden, I Paranjpe, S Somani, F Richter, ... Clin Infect Dis 71 (11), 2933-2938, 2020 | 106 | 2020 |
| WRN regulates pathway choice between classical and alternative non-homologous end joining RA Shamanna, H Lu, JK De Freitas, J Tian, DL Croteau, VA Bohr Nature communications 7 (1), 13785, 2016 | 101 | 2016 |
| Cell cycle-dependent phosphorylation regulates RECQL4 pathway choice and ubiquitination in DNA double-strand break repair H Lu, RA Shamanna, JK de Freitas, M Okur, P Khadka, T Kulikowicz, ... Nature communications 8 (1), 2039, 2017 | 81 | 2017 |
| Experimental and real-world evidence supporting the computational repurposing of bumetanide for APOE4-related Alzheimer’s disease A Taubes, P Nova, KA Zalocusky, I Kosti, M Bicak, MY Zilberter, Y Hao, ... Nature Aging 1 (10), 932-947, 2021 | 71 | 2021 |
| Federated learning of electronic health records improves mortality prediction in patients hospitalized with COVID-19 A Vaid, SK Jaladanki, J Xu, S Teng, A Kumar, S Lee, S Somani, ... MedRxiv, 2020 | 68 | 2020 |
| Hospitalised COVID-19 patients of the Mount Sinai Health System: a retrospective observational study using the electronic medical records Z Wang, A Zheutlin, YH Kao, K Ayers, S Gross, P Kovatch, S Nirenberg, ... BMJ open 10 (10), e040441, 2020 | 59 | 2020 |
| Retrospective cohort study of clinical characteristics of 2199 hospitalised patients with COVID-19 in New York City I Paranjpe, AJ Russak, JK De Freitas, A Lala, R Miotto, A Vaid, ... BMJ open 10 (11), e040736, 2020 | 37 | 2020 |
| Mount Sinai COVID Informatics Center A Lala, KW Johnson, JL Januzzi, AJ Russak, I Paranjpe, F Richter, S Zhao, ... Prevalence and impact of myocardial injury in patients hospitalized with …, 2020 | 35 | 2020 |
| Contrastive learning improves critical event prediction in COVID-19 patients T Wanyan, H Honarvar, SK Jaladanki, C Zang, N Naik, S Somani, ... Patterns 2 (12), 2021 | 31 | 2021 |
| & Glicksberg, BS (2020) A Vaid, S Somani, AJ Russak, JK De Freitas, FF Chaudhry, I Paranjpe Machine learning to predict mortality and critical events in covid-19 …, 2020 | 30 | 2020 |
| Machine learning to predict mortality and critical events in covid-19 positive new york city patients A Vaid, S Somani, AJ Russak, JK De Freitas, FF Chaudhry, I Paranjpe, ... medRxiv, 2020.04. 26.20073411, 2020 | 29 | 2020 |
| Phe2vec: Automated disease phenotyping based on unsupervised embeddings from electronic health records JK De Freitas, KW Johnson, E Golden, GN Nadkarni, JT Dudley, ... Patterns 2 (9), 2021 | 25 | 2021 |
Benjamin GlicksbergVP Data Science & Machine Learning, Character Biosciences | Adjunct Professor, Icahn School ofכתובת אימייל מאומתת בדומיין mssm.edu
