Key result
AI algorithms show potential to improve screening and early diagnosis of HF, AF, and PH.
Why the study?
Screening and early detection of CVD are crucial, and AI applications are increasingly used to handle massive healthcare datasets and improve diagnosis of various cardiovascular diseases.
Artificial intelligence algorithms demonstrate promising capabilities in enhancing the early detection and diagnosis of cardiovascular diseases, though challenges regarding accuracy, dependability, and data privacy remain.
May enhance screening for cardiovascular diseases; leaves open prospective validation of accuracy, reliability, and privacy before clinical adoption.
Screening and early detection of cardiovascular disease (CVD) are crucial for managing progress and preventing related morbidity. In recent years, several studies have reported the important role of Artificial intelligence (AI) technology and its integration into various medical sectors. AI applications are able to deal with the massive amounts of data (medical records, ultrasounds, medications, and experimental results) generated in medicine and identify novel details that would otherwise be forgotten in the mass of healthcare data sets. Nowadays, AI algorithms are currently used to improve diagnosis of some CVDs including heart failure, atrial fibrillation, hypertrophic cardiomyopathy and pulmonary hypertension. This review summarized some AI concepts, critical execution requirements, obstacles, and new applications for CVDs.
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Zargarzadeh et al. (2023) conducted a review in Cardiovascular disease. Artificial Intelligence was evaluated. Artificial intelligence algorithms demonstrate significant potential to improve the screening and early diagnosis of cardiovascular diseases such as heart failure, atrial fibrillation, and pulmonary hypertension.