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Cardiovascular disease (CVD) requires expert supervision to be effectively treated. In addition to the necessity to diagnose CVD as soon as possible, there are often cases in which patients with a substantial risk of contracting this disease are very often categorized and treated in the same way as the ones with a far lower risk. Specific symptoms often make it difficult for physicians to recognize certain forms of CVDs, and therefore correct diagnosis requires many years of experience and additional education. To contribute to the application of modern algorithms of Artificial Intelligence (AI) for the purpose of diagnosing diseases, this paper analyzed the practical application of certain algorithms and proposes a model for diagnosing CVDs. The model showed satisfactory performance, and with minor extensions and adjustments, it could be used in cardiology and family medicine clinics as an assistant to doctors.
Mušić et al. (Thu,) studied this question.
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