Ignite Creation Date:
2025-12-25 @ 3:30 AM
Ignite Modification Date:
2025-12-26 @ 2:12 AM
Study NCT ID:
NCT05682105
Status:
UNKNOWN
Last Update Posted:
2023-01-12
First Post:
2022-12-26
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Detection of Jaundice From Ocular Images Via Deep Learning
Sponsor:
Sun Yat-sen University
Organization:
Study Overview
Official Title:
Detection of Jaundice From Ocular Images Via Deep Learning : a Prospective, Multicenter Cohort Study
Status:
UNKNOWN
Status Verified Date:
2023-01
Last Known Status:
ACTIVE_NOT_RECRUITING
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
Our study presents a detection model predicting a diagnosis of jaundice (clinical jaundice and occult jaundice) trained on prospective cohort data from slit-lamp photos and smartphone photos, demonstrating the model's validity and assisting clinical workers in identifying patient underlying hepatobiliary diseases.
Detailed Description:
This study demonstrated that deep learning models could detect jaundice using ocular images in blood levels with reasonable accuracy, providing a non-invasive method for jaundice detection and recognition. This algorithm can assist clinical surgeons with daily follow-up visits and provide referral advice. It also highlights the algorithm's potential smartphone application in sizeable real-world population-based disease-detecting or telemedicine programs.
Study Oversight
Has Oversight DMC:
True
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?: