Quantifying Psychiatric Disorders with Natural Language Processing on Conversational Data
Not Applicable
Recruiting
- Conditions
- 1. Patients with major depressive disorder, bipolar I/II disorder, schizophrenia, anxiety disorders (or obsessive-compulsive disorder), and major/mild neurocognitive disorder by DSM-5 or ICD-10 2. Healthy volunteers
- Registration Number
- JPRN-UMIN000032141
- Lead Sponsor
- Keio University School of Medicine
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Recruiting
- Sex
- All
- Target Recruitment
- 500
Inclusion Criteria
Not provided
Exclusion Criteria
As patients (1) Patients whose illness can exacerbate by interview of the study. (2) Patients who have comorbidities that can interfere with measurements in the study; such as patients with dysphonia by laryngectomy. (3) Those who are considered to be ineligible by the PI or investigators. As healthy volunteers (1) Those who have comorbidities that can interfere with measurements in the study; such as patients with dysphonia by laryngectomy. (2) Those who are considered to be ineligible by the PI or investigators.
Study & Design
- Study Type
- Observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method inguistic features of each psychiatric diagnosis identified through natural language processing and machine learning
- Secondary Outcome Measures
Name Time Method