Ignite Creation Date:
2024-05-06 @ 8:16 PM
Last Modification Date:
2024-10-26 @ 3:24 PM
Study NCT ID:
NCT06314295
Status:
NOT_YET_RECRUITING
Last Update Posted:
2024-03-18
First Post:
2024-03-11
Brief Title:
Automated Echocardiographic Detection of Coronary Artery Disease Using Artificial Intelligence Methods
Sponsor:
Beijing Hospital
Organization:
Beijing Hospital
Study Overview
Official Title:
Automated Echocardiographic Detection of Coronary Artery Disease Using Artificial Intelligence Methods
Status:
NOT_YET_RECRUITING
Status Verified Date:
2024-03
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:
None
Brief Summary:
The incidence rate and mortality of coronary artery disease are increasing year by year Exploring non-invasive accurate and widely applicable methods to screen and diagnosis is of great significance New ultrasound techniques such as non-invasive myocardial work have been proven to be superior to traditional ultrasound techniques in screening and diagnosis However diagnostic analysis based on ultrasound video images is time-consuming and subjective The progress of artificial intelligence technology in fully automated quantitative evaluation of video images provides the possibility for computer-aided design screening and diagnosis At present the application of artificial intelligence in computer-aided design is a cutting-edge issue in the field of cardiovascular disease research The application of artificial intelligence technology in the construction of computer-aided diagnostic models based on ultrasound video images is still in its early stages
Detailed Description:
1 Clarify the value of new cardiac ultrasound techniques indicators in coronary artery disease diagnosis 2 To achieve classification and detection of cardiac ultrasound sections Implementing automatic segmentation and recognition of the left ventricular cavity left ventricular myocardium and left atrial wall contours through the CLAS model Using the another model to achieve heart motion tracking and synthesizing velocity vector maps of the heart flow field 3 Verify and optimize the coronary artery disease fully automated artificial intelligence diagnostic model mentioned above
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