Clinical trials: Learning Model
- Condition Learning Model
- Funder type Industry (pharma, biotech, devices)
- Age group Children (under 18)
Adolescent Well-Being, Mental Health Wellness
Predict the Best Level of Care Placement for Each Child's Behavioral Health Needs - Effectiveness Study
The purpose of this study is to test the effectiveness of a new clinical decision support tool, Placement Success Predictor (PSP), in a naturalistic setting.
- Trial name
- NCT06834763
- Testing
- Clinical team access to Placement Success Predictor (PSP) results
- Where
- United States
- Volunteers
- 403 people
- Sponsor
- Outcome Referrals, Inc.
Autism Spectrum Disorder, Depression - Major Depressive Disorder
Mental Health, Intellectual and Neurodevelopmental Disorder Detection With Artificial Intelligence Models
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)…
- Conditions
- Autism Spectrum Disorder, Depression - Major Depressive Disorder, Anxiety, Generalized, Bipolar Disorder (BD)
- Trial name
- MINDAIM (NCT06792175)
- Testing
- Solicue Machine Learning Models, Mercuria Machine Learning Models
- Where
- 2 sites in United States
- Volunteers
- 500 people
- Sponsor
- Psyrin Inc.
Adolescent Well-Being, Mental Health Wellness
Predict the Best Level of Care Placement for Each Child's Behavioral Health Needs - Efficacy Study
The purpose of this randomized clinical trial is to test the efficacy of a new clinical decision support tool, Placement Success Predictor (PSP).
- Trial name
- NCT06815562
- Testing
- Clinical team access to Placement Success Predictor (PSP) results
- Where
- United States
- Volunteers
- 213 people
- Sponsor
- Outcome Referrals, Inc.