Quantifying Psychiatric Disorders with Natural Language Processing on Conversational Data

UMIN ID: UMIN000032141

Registered date:07/04/2018

Basic Information

• Recruitment status: Recruiting
• Health condition(s) or Problem(s) studied: 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
• Date of first enrollment: 2018/04/07
• Target sample size: 500
• Countries of recruitment: Japan
• Study type: Observational

Outcome(s)

• Primary Outcome: Linguistic features of each psychiatric diagnosis identified through natural language processing and machine learning

Key inclusion & exclusion criteria

• Age minimum: 20years-old
• Age maximum: Not applicable
• Gender: Male and Female
• Exclude 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.

Related Information

• Primary Sponsor: Keio University School of Medicine
• Secondary Sponsor: Shizuoka University Oizumi hospital Oizumi mental clinic Asakadai mental clinic Tsurugaoka garden hospital Nagatsuta ikoinomori clinic Biwako hospital Sato hospital Komagino hospital Asaka hospital National Institute of Informatics University of Tokyo Tokyo Medical and Dental University
• Source(s) of Monetary Support: Japan Science and Technology Agency (JST)