S
Sulaiman Somani
Researcher at Icahn School of Medicine at Mount Sinai
Publications - 51
Citations - 2418
Sulaiman Somani is an academic researcher from Icahn School of Medicine at Mount Sinai. The author has contributed to research in topics: Risk factor & Medicine. The author has an hindex of 19, co-authored 47 publications receiving 1304 citations. Previous affiliations of Sulaiman Somani include Mount Sinai Hospital & Hasso Plattner Institute.
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Journal ArticleDOI
Prevalence and Impact of Myocardial Injury in Patients Hospitalized With COVID-19 Infection.
Anuradha Lala,Anuradha Lala,Kipp W. Johnson,James L. Januzzi,Adam Russak,Ishan Paranjpe,Felix Richter,Shan Zhao,Sulaiman Somani,Tielman Van Vleck,Akhil Vaid,Fayzan Chaudhry,Jessica K De Freitas,Zahi A. Fayad,Sean Pinney,Matthew A. Levin,Alexander W. Charney,Emilia Bagiella,Jagat Narula,Benjamin S. Glicksberg,Girish N. Nadkarni,Donna M. Mancini,Valentin Fuster +22 more
TL;DR: Cardiovascular disease (CVD) including coronary artery disease, atrial fibrillation, and heart failure, was more prevalent in patients with higher troponin concentrations, as were hypertension and diabetes.
Journal ArticleDOI
AKI in hospitalized patients with COVID-19
Lili Chan,Kumardeep Chaudhary,Aparna Saha,Kinsuk Chauhan,Akhil Vaid,Shan Zhao,Ishan Paranjpe,Sulaiman Somani,Felix Richter,Riccardo Miotto,Anuradha Lala,Arash Kia,Prem Timsina,Li Li,Robert Freeman,Rong Chen,Jagat Narula,Allan C. Just,Carol R. Horowitz,Zahi A. Fayad,Carlos Cordon-Cardo,Eric E. Schadt,Matthew A. Levin,David Reich,Valentin Fuster,Barbara Murphy,John Cijiang He,Alexander W. Charney,Erwin P. Bottinger,Benjamin S. Glicksberg,Steven G. Coca,Girish N. Nadkarni +31 more
TL;DR: This retrospective, observational study involved a review of data from electronic health records of patients aged ≥18 years with laboratory-confirmed COVID-19 admitted to the Mount Sinai Health System from February 27 to May 30, 2020 to describe the frequency of AKI and dialysis requirement, AKI recovery, and adjusted odds ratios with mortality.
Journal ArticleDOI
Coronavirus 2019 and People Living With Human Immunodeficiency Virus: Outcomes for Hospitalized Patients in New York City
Keith Sigel,Talia H. Swartz,Eddye Golden,Ishan Paranjpe,Sulaiman Somani,Felix Richter,Jessica K De Freitas,Riccardo Miotto,Shan Zhao,Paz Polak,Tinaye Mutetwa,Stephanie Factor,Saurabh Mehandru,Michael P. Mullen,Francesca Cossarini,Erwin P. Bottinger,Erwin P. Bottinger,Zahi A. Fayad,Miriam Merad,Sacha Gnjatic,Judith A. Aberg,Alexander W. Charney,Girish N. Nadkarni,Benjamin S. Glicksberg +23 more
TL;DR: No differences in adverse outcomes associated with HIV infection for hospitalized COVID-19 patients compared to a demographically similar patient group.
Journal ArticleDOI
Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation.
Akhil Vaid,Sulaiman Somani,Adam Russak,Jessica K De Freitas,Fayzan Chaudhry,Ishan Paranjpe,Kipp W. Johnson,Samuel J. Lee,Riccardo Miotto,Felix Richter,Shan Zhao,Noam D. Beckmann,Nidhi Naik,Arash Kia,Prem Timsina,Anuradha Lala,Manish Paranjpe,Eddye Golden,Matteo Danieletto,Manbir Singh,Dara Meyer,Paul F. O'Reilly,Laura M. Huckins,Patricia Kovatch,Joseph Finkelstein,Robert Freeman,Edgar Argulian,Andrew Kasarskis,Bethany Percha,Judith A. Aberg,Emilia Bagiella,Carol R. Horowitz,Barbara Murphy,Eric J. Nestler,Eric E. Schadt,Judy H. Cho,Carlos Cordon-Cardo,Valentin Fuster,Dennis S. Charney,David Reich,Erwin P. Bottinger,Erwin P. Bottinger,Matthew A. Levin,Jagat Narula,Zahi A. Fayad,Allan C. Just,Alexander W. Charney,Girish N. Nadkarni,Benjamin S. Glicksberg +48 more
TL;DR: Externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons were developed and established model interpretability to identify and rank variables that drive model predictions.
Journal ArticleDOI
Federated Learning of Electronic Health Records to Improve Mortality Prediction in Hospitalized Patients With COVID-19: Machine Learning Approach.
Akhil Vaid,Akhil Vaid,Suraj K. Jaladanki,Suraj K. Jaladanki,Jie Xu,Shelly Teng,Shelly Teng,Arvind Kumar,Arvind Kumar,Samuel J. Lee,Samuel J. Lee,Sulaiman Somani,Sulaiman Somani,Ishan Paranjpe,Ishan Paranjpe,Jessica K De Freitas,Jessica K De Freitas,Tingyi Wanyan,Tingyi Wanyan,Tingyi Wanyan,Kipp W. Johnson,Kipp W. Johnson,Mesude Bicak,Mesude Bicak,Eyal Klang,Young Joon Kwon,Anthony Costa,Shan Zhao,Riccardo Miotto,Alexander W. Charney,Erwin P. Bottinger,Erwin P. Bottinger,Erwin P. Bottinger,Zahi A. Fayad,Girish N. Nadkarni,Fei Wang,Benjamin S. Glicksberg,Benjamin S. Glicksberg +37 more
TL;DR: In this article, the authors used federated learning to predict mortality in hospitalized patients with COVID-19 within 7 days in 5 hospitals within the Mount Sinai Health System, in order to avoid locally aggregating raw clinical data across multiple institutions.