Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation

Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation

Authors of this article:

Akhil Vaid¹ ;   Sulaiman Somani¹ ;   Adam J Russak^{1, 2} ;   Jessica K De Freitas^{1, 3} ;   Fayzan F Chaudhry^{1, 3} ;   Ishan Paranjpe¹ ;   Kipp W Johnson³ ;   Samuel J Lee¹ ;   Riccardo Miotto^{1, 3} ;   Felix Richter^{1, 3} ;   Shan Zhao^{1, 4} ;   Noam D Beckmann³ ;   Nidhi Naik¹ ;   Arash Kia^{5, 6} ;   Prem Timsina^{5, 6} ;   Anuradha Lala^{5, 7} ;   Manish Paranjpe⁸ ;   Eddye Golden¹ ;   Matteo Danieletto¹ ;   Manbir Singh¹ ;   Dara Meyer³ ;   Paul F O'Reilly^{3, 9, 10} ;   Laura Huckins^{3, 9, 10} ;   Patricia Kovatch¹¹ ;   Joseph Finkelstein⁵ ;   Robert M. Freeman^{5, 6} ;   Edgar Argulian^{12, 13} ;   Andrew Kasarskis^{3, 5, 14, 15} ;   Bethany Percha² ;   Judith A Aberg^{2, 16} ;   Emilia Bagiella^{6, 7} ;   Carol R Horowitz^{2, 5} ;   Barbara Murphy² ;   Eric J Nestler^{17, 18} ;   Eric E Schadt^{3, 14} ;   Judy H Cho¹⁹ ;   Carlos Cordon-Cardo²⁰ ;   Valentin Fuster^{7, 12, 13} ;   Dennis S Charney²¹ ;   David L Reich⁴ ;   Erwin P Bottinger^{1, 22} ;   Matthew A Levin^{3, 4} ;   Jagat Narula^{12, 13} ;   Zahi A Fayad^{23, 24} ;   Allan C Just²⁵ ;   Alexander W Charney^{3, 9, 10} ;   Girish N Nadkarni^{1, 2, 19} ;   Benjamin S Glicksberg^{1, 3}