Ignite Creation Date:
2024-05-06 @ 8:26 PM
Last Modification Date:
2024-10-26 @ 3:27 PM
Study NCT ID:
NCT06383546
Status:
RECRUITING
Last Update Posted:
2024-04-25
First Post:
2024-04-22
Brief Title:
Artificial Intelligence-enabled ECG Detection of Congenital Heart Disease in Children a Novel Diagnostic Tool
Sponsor:
Xinhua Hospital Shanghai Jiao Tong University School of Medicine
Organization:
Xinhua Hospital Shanghai Jiao Tong University School of Medicine
Study Overview
Official Title:
Artificial Intelligence-enabled ECG Detection of Congenital Heart Disease in Children a Novel Diagnostic Tool
Status:
RECRUITING
Status Verified Date:
2024-04
Last Known Status:
None
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:
AI-ECG-CHD
Brief Summary:
Congenital heart disease CHD is the most common congenital disease in children The early detection diagnosis and treatment of CHD in children is of great significance to improve the prognosis and reduce the mortality of children but the current screening methods have limitations Electrocardiogram ECG as an economical and rapid means of heart disease detection has a very important value in the auxiliary diagnosis of CHDBig data and deep learning technologies in artificial intelligence AI have shown great potential in the medical field The advent of the big data era provides rich data resources for the in-depth study of CHD ECG signals in children The development of deep learning technology especially the breakthrough in the field of image recognition provides a strong technical support for the intelligent analysis of electrocardiogram The particularity of children electrocardiogram requires the development of a special algorithm model At present the research on the application of deep learning models to identify childrens electrocardiograms is limited and the training and verification from large data sets are lacking Based on the Chinese Congenital Heart Disease Collaborative Research Network this project aims to integrate data and deep learning technology to develop a set of intelligent electrocardiogram assisted diagnosis system CHD-ECG AI system suitable for children with CHD so as to improve the early detection rate of CHD and improve the efficiency of congenital heart disease screening
Detailed Description:
None
Study Oversight
Has Oversight DMC:
None
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?:
None