Artificial Intelligence Clinical Trial
Official title:
Artificial Intelligence-enabled ECG Detection of Congenital Heart Disease in Children: a Novel Diagnostic Tool
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 CHD.Big 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 children's 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.
n/a
| Status | Clinical Trial | Phase | |
|---|---|---|---|
| Completed |
NCT04589078 -
Polyp REcognition Assisted by a Device Interactive Characterization Tool - The PREDICT Study
|
||
| Completed |
NCT03857438 -
Correlation of Audiovisual Features With Clinical Variables and Neurocognitive Functions in Bipolar Disorder, Mania
|
||
| Completed |
NCT04735055 -
Artificial Intelligence Prediction for the Severity of Acute Pancreatitis
|
||
| Not yet recruiting |
NCT05452993 -
Screening for Diabetic Retinopathy in Pharmacies With Artificial Intelligence Enhanced Retinophotography
|
N/A | |
| Not yet recruiting |
NCT04337229 -
Evaluation of Comfort Behavior Levels of Newborns With Artificial Intelligence Techniques
|
N/A | |
| Completed |
NCT05687318 -
A Clinical Trial of the Effectiveness and Safety of Software Assisting Diagnose the Intestinal Polyp Digestive Endoscopy by Analysis of Colonoscopy Medical Images From Electronic Digestive Endoscopy Equipment
|
N/A | |
| Recruiting |
NCT06051682 -
Optimization of the Diagnosis of Bone Fractures in Patients Treated in the Emergency Department by Using Artificial Intelligence for Reading Radiological Images in Comparison With Traditional Reading by the Emergency Doctor.
|
N/A | |
| Not yet recruiting |
NCT06039917 -
Effect of the Automatic Surveillance System on Surveillance Rate of Patients With Gastric Premalignant Lesions
|
N/A | |
| Not yet recruiting |
NCT06362629 -
AI App for Management of Atopic Dermatitis
|
N/A | |
| Recruiting |
NCT06164002 -
A I in the Prediction of Clinical Performance, Marginal Fit and Fracture Resistance of Vertical Versus Horizontal Margin Designs Fabricated With 2 Ceramic Materials
|
N/A | |
| Recruiting |
NCT06059378 -
Real-life Implementation of an AI-based Optical Diagnosis
|
N/A | |
| Completed |
NCT05517889 -
Repeatability and Stability of Healthy Skin Features on OCT
|
||
| Completed |
NCT04816981 -
AI-EBUS-Elastography for LN Staging
|
N/A | |
| Completed |
NCT05006092 -
Surveillance Modified by Artificial Intelligence in Endoscopy (SMARTIE)
|
N/A | |
| Recruiting |
NCT04535466 -
Diagnosis Predictive Modle for Dense Density Breast Tissue Based on Radiomics
|
||
| Enrolling by invitation |
NCT04719117 -
Retrograde Cholangiopancreatography AI Assisted System Validation on Effectiveness and Safety
|
||
| Completed |
NCT04399590 -
Comparing the Number of False Activations Between Two Artificial Intelligence CADe Systems: the NOISE Study
|
||
| Recruiting |
NCT04126265 -
Artificial Intelligence-assisted Colonoscopy for Detection of Colon Polyps
|
N/A | |
| Recruiting |
NCT06255808 -
Development of Assist Tool for Breast Examination Using the Principle of Ultrasonic Sensor
|
||
| Recruiting |
NCT04131530 -
Automatic Evaluation of Inflammation Activity in Ulcerative Colitis Using pCLE With Artificial Intelligence
|