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临床试验/NCT06792175
NCT06792175Enrolling By Invitation不适用

Mental Health, Intellectual and Neurodevelopmental Disorder Detection With Artificial Intelligence Models: Testing Speech-Based Machine Learning Algorithms for Clinical Assessment and Risk Stratification in Mental Health Presentations

Psyrin Inc.2 个研究点 分布在 1 个国家目标入组 500 人开始时间: 2025年2月4日最近更新:
适应症

试验速览

阶段
不适用
状态
Enrolling By Invitation
发起方
入组人数
500
试验地点
2
主要终点
Clinical diagnosis

研究概览

简要总结

This study investigates whether AI-driven analysis of speech can accurately predict clinical diagnoses and assess risk for various mental or behavioral health conditions, including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, bipolar disorder, generalized anxiety disorder, major depressive disorder, obsessive compulsive disorder (OCD), post-traumatic stress disorder (PTSD), and schizophrenia. We aim to develop tools that can support clinicians in making more accurate and efficient diagnoses.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
13 Years 至 60 Years(Child, Adult)
性别
All
接受健康志愿者
否

入选标准

  • 未提供

排除标准

  • 未提供

结局指标

主要结局

Clinical diagnosis

时间窗: 0 months, 3 months, 6 months

Clinician diagnosis will be recorded for each participant at first assessment, 3-month, and 6-month follow-up. Diagnoses will be made according to ICD-11 or DSM-5 criteria for the compatible disorders: ADHD, ASD, BPAD, GAD, MDD, OCD, PTSD, and SSD. Additional relevant labels such as other mental health disorders, clinical high risk (CHR) and substance use may be recorded.

Performance of AI models

时间窗: 0 months, 3 months, 6 months

The performance of the Mercuria and Solicue AI models will be evaluated using performance metrics of accuracy, balanced accuracy, sensitivity (recall), specificity, positive predictive value (precision), negative predictive value, F1 score, AUC-ROC. Predicted labels will be compared with the ground truth clinical diagnoses obtained from the participating mental health clinics. Confidence acceptance threshold will be set.

Speech Battery ("PSY-10") audio

时间窗: At initial assessment

The speech battery consists of prompt-based tasks designed to elicit speech responses from participants in the form of monologues. This includes text reading, recall, and picture description tasks.

次要结局

  • Mood Disorder Questionnaire (MDQ)(At initial assessment)
  • Patient Health Questionnaire-9 (PHQ-9)(At initial assessment)
  • DSM-5 Level 1 Cross-Cutting Symptom Measure (DSM-XC)(At initial assessment)
  • Reported Distress(After initial assessment)

研究者

发起方
Psyrin Inc.
申办方类型
Industry
责任方
Sponsor

研究点 (2)

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