PERCEPTION AND UTILIZATION OF AI-BASED DIAGNOSTIC TOOLS AMONG PRACTICING CARDIOLOGISTS

Abstract

Background: Artificial intelligence (AI) is rapidly transforming cardiovascular diagnostics through enhanced precision, speed, and pattern recognition. Despite the growing presence of AI tools, their real-world adoption among practicing cardiologists remains unclear, particularly in high-volume tertiary care environments.

Objective: To assess the awareness, acceptance, and clinical utilization of AI-based diagnostic tools among cardiologists working in a tertiary care hospital setting.

Methods: A cross-sectional study was conducted over eight months at a tertiary care hospital in Lahore. A structured, pre-validated questionnaire was administered to 150 board-certified cardiologists. The instrument captured data on demographics, awareness, attitudes, and real-world application of AI tools. Data were analyzed using SPSS version 26. Descriptive statistics, chi-square tests, and ANOVA were used, with p-values <0.05 considered significant.

Results: Of the 150 respondents, 74.7% were male with a mean age of 42.6 ± 6.9 years. High awareness was observed for AI-enabled ECG (82.0%), echocardiography tools (73.3%), and risk prediction models (78.7%). Acceptance levels were also favorable, with 74.7% supporting routine AI integration and 72.0% agreeing AI improves diagnostic accuracy. Despite this, only 58.0% used AI-enabled ECGs, 49.3% used risk stratification tools, and 43.3% used AI in echocardiography; 24.0% reported not using any AI tool. The main barriers included lack of training and workflow integration.

Conclusion: Cardiologists in tertiary care demonstrate substantial awareness and positive perceptions of AI diagnostics, though practical adoption lags. Focused training and institutional strategies are needed to bridge this implementation gap and maximize clinical benefit.