Ignite Creation Date:
2024-10-26 @ 3:35 PM
Last Modification Date:
2024-10-26 @ 3:35 PM
Study NCT ID:
NCT06511713
Status:
RECRUITING
Last Update Posted:
None
First Post:
2024-07-15
Brief Title:
AI-Assisted Rapid Warning for Mental Disorders Based on High-Resolution Fundus Imaging and High-Speed Eye-Tracking
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Artificial Intelligence-Assisted Rapid Warning for Mental Disorders Based on High-Resolution Fundus Images and High-Speed Eye-Tracking Trajectories
Status:
RECRUITING
Status Verified Date:
2024-07
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
This project aims to collect eye-tracking trajectories and fundus imaging data from individuals seeking mental health services By utilizing artificial intelligence combining dynamic eye-tracking and static fundus data and employing convolutional neural network analysis methods the investigators will develop models for the classification and early warning of common mental disorders These models will assist clinicians in making objective diagnoses of common mental disorders and in predicting the risk of adverse outcomes thereby addressing the significant technical bottleneck of the current lack of objective diagnostic and warning instruments for mental disorders
Detailed Description:
The investigators have completed the construction of the eye-tracking diagnostic and warning system and have piloted the new system The plan is to recruit 1000 individuals at Clinical High Risk for Psychosis CHR for model validation of predictive outcomes and 1000 patients with common mental disorders for model validation of diagnostic classification This cohort includes 300 patients with schizophrenia 300 patients with affective disorders 200 patients with anxiety disorders and 200 patients with cognitive impairment in the elderly The system will also directly connect with the investigators previous research data collection system and be deployed in no fewer than one hospitals healthcare system Additionally variables that may affect the accuracy of results will be fine-tuned to ensure that the eye-tracking and fundus system more accurately reflects actual clinical conditions The application of the system will revolve around a big data analysis platform and seamlessly integrate with the existing hospital information systems designing real-time feedback report modules to assist clinicians in making objective diagnoses efficiently and effectively
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None