A Study to Evaluate Accuracy and Validity of the Chang Gung ECG Abnormality Detection Software

• Status: Not yet recruiting
• Trial end date: 2023-12-10
• Target enrollment: 0
• Participant gender: All

Summary

"Chang Gung ECG Abnormality Detection Software" is a is an artificial intelligence medical signal analysis software that detect whether patients have abnormal ECG signals of 14 diseases by static 12-lead ECG. The 14 diseases were

• Long QT syndrome

• Sinus bradycardia

• Sinus Tachycardia

• Premature atrial complexes

• Premature ventricular complexes

• Atrial Flutter, Right bundle branch block

• Left bundle branch block

• Left Ventricular hypertrophy

• Anterior wall Myocardial Infarction

• Septal wall Myocardial Infarction

• Lateral wall Myocardial Infarction

• Inferior wall Myocardial Infarction

• Posterior wall Myocardial Infarction

The main purpose of this study is to verify whether "Chang Gung ECG Abnormality Detection Software" can correctly identify abnormal ECG signals among patients of 14 diseases. The interpretation standard is the consensus of 3 cardiologists. The results of the software analysis will be used to evaluate the performance of the primary and secondary evaluation indicators.

• Phase: N/A
• Accepts Healthy Volunteers?: No

Details

• Lead Sponsor: Chang Gung Memorial Hospital

Criteria

Inclusion Criteria:

• Equal or greater than twenty years old.

• Static 12-lead electrocardiogram of General Electric MUSE XML format file.

• The data comes from the static 12-lead electrocardiogram device of General Electric (model MAC5500).

• The electrocardiogram signal is 500 Hz.

• The Alternating current (AC) filter of the electrocardiogram signal is 60 Hz.

• The resource of original diagnosis was a cardiologist.

Exclusion Criteria:

• Cases used in the model development process.

• Lacks any electrode.

• Contain any electrode lacks a segment.