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Artificial intelligence (AI) is a fast-growing technology that has great potential for advancements in cardiovascular medicine. Cardiovascular diseases (CVDs) are currently diagnosed through a comprehensive patient evaluation that includes a review of the patient's medical history, biomarker analysis, physical examinations, and specialized testing. The clinical expertise and experience of medical practitioners are required for the interpretation of test results, and the findings are used to devise treatment plans for patients. However, the efficacy of this strategy has been brought into question owing to variations in the way healthcare professionals perform the treatment and the likelihood of errors. By integrating AI into the healthcare domain, workflow efficiency, cost-effectiveness, and decision-making across various scientific disciplines, including medicine, can be significantly enhanced. Although the potential advantages of AI in cardiovascular care are substantial, it is essential to recognize and tackle the existing constraints. AI models necessitate access to superior and varied datasets, which might pose difficulties in acquisition due to data accessibility, privacy considerations, and the requirement for standardized data formats. Moreover, the comprehensibility of AI algorithms is crucial in order to establish confidence and promote cooperation between AI systems and healthcare practitioners. This article presents an overview of AI in the context of cardiovascular care, discussing its potential applications, current limitations, and future directions.
Yousef Alharbi (Mon,) studied this question.