BACKGROUND: This study aimed to compare multiple quantitative evaluation indices of levels of theoretical knowledge and clinical practice skills in training medical interns in cardiovascular imaging based on the use of the blended teaching (BT) online artificial intelligence (AI) case resource network platform (CRNP), including time and frequency indices and effectiveness of the CRNP.

MATERIAL AND METHODS: The study included 110 medical interns who were divided into the routine teaching (RT) group (n=55) and the blended teaching (BT) group (n=55). The two were assessed using the mini-clinical evaluation exercise (mini-CEX) that assessed clinical skills, attitudes, and behaviors and using an objective written questionnaire. The following four indices were compared between the RT and BT groups: the X-ray score (XS), the computed tomography angiography (CTA) score (CS), the cardiac magnetic resonance imaging (CMRI) score (MS), and the average score (AS). Seven assessment indicators included: the imaging description (ID), the qualitative diagnosis (QD), the differential diagnosis (DD), examination preparation (EP), interview skill (IS), position display (PD), and human care (HC). Indicators of CRNP use included: number of times (TN), average duration (AD), single maximum duration (SMD), and total duration (TD).

RESULTS: AS significantly correlated with AD (rAD=0.761) and TD (rTD=0.754), and showed moderate correlation with TN (rTN=0.595), but weak correlation with SMD (rSMD=0.404).

CONCLUSIONS: Levels of theoretical knowledge and clinical practice skills during medical intern training in cardiovascular imaging based on BT using the CRNP teaching technology improved theoretical knowledge and practical skills.

Keywords: Artificial Intelligence, Cardiac Imaging Techniques, Teaching, Cardiology, Cardiovascular Diseases, Clinical Competence, Computer Systems, Diagnostic Imaging, Diagnostic Techniques, Cardiovascular, Education, Medical, Graduate, Internship and Residency