HeartBEiT: Vision Transformer for Electrocardiogram Data Improves Diagnostic Performance at Low Sample Sizes. - Akhil Vaid; Joy Jiang; Ashwin Sawant; Stamatios Lerakis; Edgar Argulian; Yuri Ahuja; Joshua Lampert; Alexander Charney; Hayit Greenspan; Benjamin S. Glicksberg; Jagat Narula; Girish N. Nadkarni (CoRR, 2022)

Autoencoders for sample size estimation for fully connected neural network classifiers. - Faris F. Gulamali; Ashwin Sawant; Patricia H. Kovatch; Benjamin S. Glicksberg; Alexander Charney; Girish N. Nadkarni; Eric K. Oermann (npj Digit. Medicine, 2022)

Online Unsupervised Representation Learning of Waveforms in the Intensive Care Unit via a novel cooperative framework: Spatially Resolved Temporal Networks (SpaRTEn). - Faris F. Gulamali; Ashwin Sawant; Ira S. Hofer; Matthew A. Levin; Alexander Charney; Karandeep Singh; Benjamin S. Glicksberg; Girish N. Nadkarni (MLHC, 2023)

An AI-Guided Data Centric Strategy to Detect and Mitigate Biases in Healthcare Datasets. - Faris F. Gulamali; Ashwin S. Sawant; Lora Liharska; Carol R. Horowitz; Lili Chan; Patricia H. Kovatch; Ira S. Hofer; Karandeep Singh; Lynne D. Richardson; Emmanuel Mensah; Alexander W. Charney; David L. Reich; et al. (CoRR, 2023)

A foundational vision transformer improves diagnostic performance for electrocardiograms. - Akhil Vaid; Joy Jiang; Ashwin Sawant; Stamatios Lerakis; Edgar Argulian; Yuri Ahuja; Joshua Lampert; Alexander Charney; Hayit Greenspan; Jagat Narula; Benjamin S. Glicksberg; Girish N. Nadkarni (npj Digit. Medicine, 2023)

Generative Large Language Models are autonomous practitioners of evidence-based medicine. - Akhil Vaid; Joshua Lampert; Juhee Lee; Ashwin Sawant; Donald Apakama; Ankit Sakhuja; Ali Soroush; Denise Lee; Isotta Landi; Nicole Bussola; Ismail Nabeel; Robbie Freeman; et al. (CoRR, 2024)

Evaluating the accuracy of a state-of-the-art large language model for prediction of admissions from the emergency room. - Benjamin S. Glicksberg; Prem Timsina; Dhaval Patel; Ashwin Sawant; Akhil Vaid; Ganesh Raut; Alexander W. Charney; Donald Apakama; Brendan G. Carr; Robert Freeman; Girish N. Nadkarni; Eyal Klang (J. Am. Medical Informatics Assoc., 2024)

Derivation, external and clinical validation of a deep learning approach for detecting intracranial hypertension. - Faris F. Gulamali; Pushkala Jayaraman; Ashwin S. Sawant; Jacob Desman; Benjamin Fox; Annette Chang; Brian Y. Soong; Naveen Arivazagan; Alexandra S. Reynolds; Son Q. Duong; Akhil Vaid; Patricia H. Kovatch; et al. (npj Digit. Medicine, 2024)

A distributional reinforcement learning model for optimal glucose control after cardiac surgery. - Jacob Desman; Zhang-Wei Hong; Moein Sabounchi; Ashwin S. Sawant; Jaskirat Gill; Ana C. Costa; Gagan Kumar; Rajeev Sharma; Arpeta Gupta; Paul McCarthy; Veena Nandwani; Doug Powell; et al. (npj Digit. Medicine, 2025)