This paper is in the following e-collection/theme issue:

Diagnostic Tools in Mental Health (283) Machine Learning (1764) Bipolar Disorders (66) Psychotic Disorders (180) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1835) Methods and New Tools in Mental Health Research (501) New Methods (1034) Psychiatry (76)

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

Authors of this article:

Michael L Birnbaum1, 2, 3 Author Orcid Image ;   Avner Abrami4 Author Orcid Image ;   Stephen Heisig5 Author Orcid Image ;   Asra Ali1, 2 Author Orcid Image ;   Elizabeth Arenare1, 2 Author Orcid Image ;   Carla Agurto4 Author Orcid Image ;   Nathaniel Lu1, 2 Author Orcid Image ;   John M Kane1, 2, 3 Author Orcid Image ;   Guillermo Cecchi4 Author Orcid Image
Article Authors Cited by (22) Tweetations (11) Metrics

Journals

  1. Granrud O, Rodriguez Z, Cowan T, Masucci M, Cohen A. Alogia and pressured speech do not fall on a continuum of speech production using objective speech technologies. Schizophrenia Research 2023;259:121 View
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  8. Olah J, Cummins N, Arribas M, Gibbs-Dean T, Molina E, Sethi D, Kempton M, Morgan S, Spencer T, Diederen K. Towards a scalable approach to assess speech organization across the psychosis-spectrum -online assessment in conjunction with automated transcription and extraction of speech measures. Translational Psychiatry 2024;14(1) View
  9. Alsuhaibani M, Dodge H, Mahoor M. Mild cognitive impairment detection from facial video interviews by applying spatial-to-temporal attention module. Expert Systems with Applications 2024;252:124185 View
  10. Perini I, Pabst A, Martinez D, Maurage P, Heilig M. Modeling social cognition in alcohol use disorder: lessons from schizophrenia. Psychopharmacology 2025;242(5):1157 View
  11. Aina J, Akinniyi O, Rahman M, Odero-Marah V, Khalifa F. A Hybrid Learning-Architecture for Mental Disorder Detection Using Emotion Recognition. IEEE Access 2024;12:91410 View
  12. Kaczmarek‐Majer K, Dominiak M, Antosik A, Hryniewicz O, Kamińska O, Opara K, Owsiński J, Radziszewska W, Sochacka M, Święcicki Ł. Acoustic features from speech as markers of depressive and manic symptoms in bipolar disorder: A prospective study. Acta Psychiatrica Scandinavica 2025;151(3):358 View
  13. Ortiz A, Halabi R, Alda M, Burgos A, DeShaw A, Gonzalez-Torres C, Husain M, O'Donovan C, Tolend M, Hintze A, Mulsant B. Day-to-day variability in sleep and activity predict the onset of a hypomanic episode in patients with bipolar disorder. Journal of Affective Disorders 2025;374:75 View
  14. Briganti G, Lechien J. Voice Quality as Digital Biomarker in Bipolar Disorder: A Systematic Review. Journal of Voice 2025 View
  15. Nasrallah M, El Moghrabi A, Kayal M, Matar D, Alwan I, Fakhoury M. The emerging role of artificial intelligence in the diagnosis and treatment of autism spectrum disorder and attention-deficit/hyperactivity disorder. International Journal of Developmental Disabilities 2025:1 View
  16. Mosolova E, Alfimov A, Kostyukova E, Mosolov S. Prospects of machine learning applications in affective disorders. Digital Diagnostics 2025;6(1):97 View
  17. Friedrich M, Relton S, Wong D, Alty J. Computer Vision in Clinical Neurology. JAMA Neurology 2025;82(4):407 View
  18. Crocamo C, Cioni R, Canestro A, Nasti C, Palpella D, Piacenti S, Bartoccetti A, Re M, Simonetti V, Barattieri di San Pietro C, Bulgheroni M, Bartoli F, Carrà G. Acoustic and Natural Language Markers for Bipolar Disorder: A Pilot, mHealth Cross-Sectional Study. JMIR Formative Research 2025;9:e65555 View
  19. Song J, He M, Zheng X, Zhang Y, Bi C, Feng J, Du J, Li H, Shen B. Face-based machine learning diagnostics: applications, challenges and opportunities. Artificial Intelligence Review 2025;58(8) View

Conference Proceedings

  1. Brooks J, Tiruvadi V, Baird A, Tzirakis P, Li H, Gagne C, Oh M, Cowen A. International Cconference on Multimodal Interaction. Emotion Expression Estimates to Measure and Improve Multimodal Social-Affective Interactions View
  2. Adjailia F, Hadri S, Bbouramoul A. 2023 World Symposium on Digital Intelligence for Systems and Machines (DISA). Understanding the Interplay of Clinical Features and Cognitive Behavior in Schizophrenia: A Machine Learning Study View
  3. Kumar R, Bordoloi D, Shrivastava A, Kumar C, Kumari V, Kumar A. 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON). Behavioral and Clinical Data Analysis for Autism Spectrum Disorder Screening with Machine Learning View