Cardiovascular diseases are one of the leading causes of death worldwide. Detecting them early is essential to improve treatment and prevent serious complications. However, diagnosis can be complex and, in some cases, delayed, which affects patient care.\u00a0In recent years, several studies have explored the use of artificial intelligence models to assist in the diagnosis of cardiovascular diseases. Although many of these models have shown promising results, there is still uncertainty about how effective they are overall and whether their findings are consistent across different studies.<\/p>\n
Researchers conducted a systematic review and meta-analysis following international standards. They analyzed thousands of scientific studies and selected 35 investigations that evaluated artificial intelligence models for diagnosing different cardiovascular conditions, including coronary artery disease, heart attack, and heart failure.\u00a0The results showed that, on average, artificial intelligence models have a strong ability to distinguish between individuals with and without cardiovascular disease. In several studies, diagnostic sensitivity was high, particularly when electrocardiogram data were used.<\/p>\n
These findings suggest that artificial intelligence could help improve the accuracy and speed of diagnosing cardiovascular diseases, potentially enabling more timely clinical decision-making.\u00a0The authors note that further studies with validation in different clinical settings are still needed to confirm that these models work reliably before being widely implemented in medical practice.<\/p>\n