The Role of Artificial Intelligence in Early Detection of Cardiovascular Diseases

Abstract

Introduction: Cardiovascular diseases (CVDs) are a leading cause of morbidity and mortality worldwide. Early diagnosis is crucial for better patient outcomes and effective care. Artificial intelligence (AI) has emerged as a viable method in cardiology that enhances risk assessment and diagnostic accuracy..
Objectives: This study compares the accuracy, sensitivity, and specificity of AI-assisted diagnostics with conventional techniques in order to assess the usefulness of AI in the early diagnosis of CVDs.
Materials and Methods: From January to June 2024, an observational study was carried out at NICVD Karachi Pakistan. 500 patients' ECG and echocardiogram data were examined using AI algorithms, and the results were compared to evaluations made by cardiologists.
Results: AI performed better than conventional diagnostic techniques, showing increased sensitivity (94.2%) and specificity (91.5%). 20.8% of preclinical anomalies were successfully identified by AI, resulting in earlier actions..
Conclusion: Early CVD detection is much improved by AI, which also increases diagnostic accuracy. For wider clinical adoption, data bias, ethical issues, and implementation hurdles must be addressed.