Published on in Vol 9, No 1 (2022): January
![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](https://asset.jmir.pub/assets/2e3de056e3d980a8d052dd31404f8a37.png 480w,https://asset.jmir.pub/assets/2e3de056e3d980a8d052dd31404f8a37.png 960w,https://asset.jmir.pub/assets/2e3de056e3d980a8d052dd31404f8a37.png 1920w,https://asset.jmir.pub/assets/2e3de056e3d980a8d052dd31404f8a37.png 2500w)
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