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

RCTs - Protocols/Proposals (funded, already peer-reviewed, eHealth) (355) New Methods (972) Artificial Intelligence (1466) Mental Health Issues in Adolescence (466) Machine Learning (1524)

Published on in Vol 12 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51912, first published .
Objectively Quantifying Pediatric Psychiatric Severity Using Artificial Intelligence, Voice Recognition Technology, and Universal Emotions: Pilot Study for Artificial Intelligence-Enabled Innovation to Address Youth Mental Health Crisis

Objectively Quantifying Pediatric Psychiatric Severity Using Artificial Intelligence, Voice Recognition Technology, and Universal Emotions: Pilot Study for Artificial Intelligence-Enabled Innovation to Address Youth Mental Health Crisis

Objectively Quantifying Pediatric Psychiatric Severity Using Artificial Intelligence, Voice Recognition Technology, and Universal Emotions: Pilot Study for Artificial Intelligence-Enabled Innovation to Address Youth Mental Health Crisis

Authors of this article:

Desmond Caulley1 Author Orcid Image ;   Yared Alemu2, 3 Author Orcid Image ;   Sedara Burson2 Author Orcid Image ;   Elizabeth Cárdenas Bautista2, 3 Author Orcid Image ;   Girmaw Abebe Tadesse4 Author Orcid Image ;   Christopher Kottmyer1 Author Orcid Image ;   Laurent Aeschbach1 Author Orcid Image ;   Bryan Cheungvivatpant1 Author Orcid Image ;   Emre Sezgin5 Author Orcid Image
Article Authors Cited by (2) Tweetations (4) Metrics

Journals

  1. Zahavi I, Ben Shitrit I, Einav S. Using augmented intelligence to improve long term outcomes. Current Opinion in Critical Care 2024;30(5):523 View
  2. Kerth J, Hagemeister M, Bischops A, Reinhart L, Dukart J, Heinrichs B, Eickhoff S, Meissner T. Artificial intelligence in the care of children and adolescents with chronic diseases: a systematic review. European Journal of Pediatrics 2024;184(1) View