Published on in Vol 9, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24699, first published .
Acoustic and Facial Features From Clinical Interviews for Machine Learning–Based Psychiatric Diagnosis: Algorithm Development

Acoustic and Facial Features From Clinical Interviews for Machine Learning–Based Psychiatric Diagnosis: Algorithm Development

Acoustic and Facial Features From Clinical Interviews for Machine Learning–Based Psychiatric Diagnosis: Algorithm Development

Michael L Birnbaum   1, 2, 3 * , MD ;   Avner Abrami   4 * , MSc ;   Stephen Heisig   5 , BSc ;   Asra Ali   1, 2 , MA ;   Elizabeth Arenare   1, 2 , BA ;   Carla Agurto   4 , PhD ;   Nathaniel Lu   1, 2 , MA ;   John M Kane   1, 2, 3 * , MD ;   Guillermo Cecchi   4 * , PhD

1 Department of Psychiatry, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, United States

2 The Feinstein Institute for Medical Research, Northwell Health, Manhasset, NY, United States

3 The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States

4 Computational Biology Center, IBM Research, Yorktown Heights, NY, United States

5 Icahn School of Medicine at Mount Sinai, New York City, NY, United States

*these authors contributed equally

Corresponding Author:

  • Michael L Birnbaum, MD
  • Department of Psychiatry
  • The Zucker Hillside Hospital
  • Northwell Health
  • 75-59 263rd St
  • Glen Oaks, NY, 11004
  • United States
  • Phone: 1 7184708305
  • Email: mbirnbaum@northwell.edu