AI Models for Mental Health and Neurodevelopmental Disorder Detection
This study is looking at whether artificial intelligence (AI) models, called Solicue Machine Learning Models and Mercuria Machine Learning Models, can help doctors more accurately and efficiently diagnose various mental health conditions. These conditions include Autism Spectrum Disorder, depression (Major Depressive Disorder), anxiety (Generalized Anxiety Disorder), Bipolar Disorder, and Attention Deficit Hyperactivity Disorder (ADHD), among others. The study will analyze speech patterns to see if the AI can predict clinical diagnoses and assess risk for these conditions. You might be able to join if you are between 13 and 60 years old, are currently being assessed for a mental or behavioral health condition, and are fluent in English. The researchers will measure how well the AI models perform compared to clinical diagnoses over 0, 3, and 6 months. The current recruitment status is unclear.
- Study design
- This is an observational study with a planned enrollment of 500 participants. It is not specified if the study is randomized or blinded.
- What's involved
- You will participate in an initial assessment that includes a speech battery audio recording. Your clinical diagnosis and the performance of the AI models will be assessed at 0, 3, and 6 months.
- Compensation
- Not stated in the trial record.
- Follow-up
- Participants will be followed for 6 months after their initial assessment.
AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.
Mental Health, Intellectual and Neurodevelopmental Disorder Detection With Artificial Intelligence Models
At a glance
Conditions
NCT06792175
Where you'd take part
This study runs at 2 sites. They're the same protocol — you choose where, and that choice sets who your contact draft is addressed to.
Allwell Behavioral Health Services
Zanesville, Ohiono site contact published
The Brookline Center
Brookline, Massachusettsno site contact published
Sites open and close at different times, so the status above is per site — it can differ from the study's overall status.
Study leadership
- Julianna Olah, B.Sc., M.A., M.Sc., Ph.D. · PRINCIPAL_INVESTIGATOR · Psyrin Inc.
- Atta-ul Raheem R Chaudhry, B.Sc. (Hons.), M.B.B.S. · PRINCIPAL_INVESTIGATOR · Psyrin Inc.
Who to contact
This trial hasn't published a contact. View it on ClinicalTrials.gov
What this trial measures
- Speech Battery ("PSY-10") audioAt 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.
- Clinical diagnosis0 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 models0 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.