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, US

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

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

4 Computational Biology Center, IBM Research , Yorktown Heights, NY, US

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

*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
  • US
  • Phone: 1 7184708305
  • Email: mbirnbaum@northwell.edu