New developments in machine learning-based analysis of speech can be hypothesized to facilitate the long-term monitoring of major depressive disorder (MDD) during and after treatment. To test this hypothesis, we collected 550 speech samples from tele...
BACKGROUND: The purpose of this study is to examine the validity, reliability and methodological quality of delirium scales that have been translated and adapted in China using quality assessment tools.
BACKGROUND: The Chat Generative Pre-trained Transformer (ChatGPT), an artificial intelligence-based web application, has demonstrated substantial potential across various knowledge domains, particularly in medicine. This cross-sectional study assesse...
Revista brasileira de psiquiatria (Sao Paulo, Brazil : 1999)
39074334
OBJECTIVE: Verbal communication contains key information for mental health assessment. Researchers have linked psychopathology phenomena to certain counterparts in natural language processing. We characterized subtle impairments in the early stages o...
The Symptom Checklist-90 (SCL-90), widely utilized for psychological assessments, faces challenges due to its extensive nature. Streamlining the SCL-90 is essential in order to enhance its practicality without compromising its broad applicability acr...
BACKGROUND: Psychiatry faces a challenge due to the lack of objective biomarkers, as current assessments are based on subjective evaluations. Automated speech analysis shows promise in detecting symptom severity in depressed patients. This project ai...
Recently, methods of quickly and accurately screening for geriatric depression have attracted substantial attention. Short forms of the 30-item Geriatric Depression Scale have been developed based on classical test theory, such as the GDS-4, GDS-5, a...
Major Depressive Disorder (MDD) is a prevalent mental health condition that often begins in adolescence, with significant long-term implications. Indicated prevention programs targeting adolescents with mild symptoms have shown efficacy, yet the meth...
OBJECTIVES: Interpatient variability in bipolar I depression (BP-D) symptoms challenges the ability to predict pharmacotherapeutic outcomes. A machine learning workflow was developed to predict remission after 8 weeks of pharmacotherapy (total score ...
OBJECTIVE: To develop a stratified screening tool through machine learning approaches for the Center for Epidemiologic Studies Depression Scale (CES-D-20) while maintaining diagnostic accuracy, addressing the efficiency limitations in large-scale app...