Artificial Intelligence-Based Clinical Decision Support Systems in Cardiovascular Diseases

被引:7
|
作者
Bozyel, Serdar [1 ]
Simsek, Evrim [2 ]
Kocyigit, Duygu [3 ]
Guler, Arda [4 ]
Korkmaz, Yetkin [5 ]
Seker, Mehmet [5 ]
Erturk, Mehmet [4 ]
Keser, Nurgul [5 ]
机构
[1] Hlth Sci Univ, Kocaeli City Hosp, Dept Cardiol, Kocaeli, Turkiye
[2] Ege Univ, Fac Med, Dept Cardiol, Izmir, Turkiye
[3] Hlth Sci Univ, Ankara City Hosp, Dept Cardiol, Ankara, Turkiye
[4] Hlth Sci Univ, Mehmet Akif Ersoy Training & Res Hosp, Dept Cardiol, Istanbul, Turkiye
[5] Hlth Sci Univ, Sultan Abdulhamid Han Training & Res Hosp, Dept Cardiol, Istanbul, Turkiye
来源
ANATOLIAN JOURNAL OF CARDIOLOGY | 2024年 / 28卷 / 02期
关键词
Artificial intelligence; clinical decision support systems; cardiovascular diseases; patient management; prediction; ATRIAL-FIBRILLATION; PRIMARY-CARE; HYPERTROPHIC CARDIOMYOPATHY; GLOBAL BURDEN; ELECTROCARDIOGRAM; PERFORMANCE; ALGORITHM;
D O I
10.14744/AnatolJCardiol.2023.3685
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Despite all the advancements in science, medical knowledge, healthcare, and the healthcare industry, cardiovascular disease (CVD) remains the leading cause of morbidity and mortality worldwide. The main reasons are the inadequacy of preventive health services and delays in diagnosis due to the increasing population, the failure of physicians to apply guide-based treatments, the lack of continuous patient follow-up, and the low compliance of patients with doctors' recommendations. Artificial intelligence (AI)-based clinical decision support systems (CDSSs) are systems that support complex decision-making processes by using AI techniques such as data analysis, foresight, and optimization. Artificial intelligence-based CDSSs play an important role in patient care by providing more accurate and personalized information to healthcare professionals in risk assessment, diagnosis, treatment optimization, and monitoring and early warning of CVD. These are just some examples, and the use of AI for CVD decision support systems is rapidly evolving. However, for these systems to be fully reliable and effective, they need to be trained with accurate data and carefully evaluated by medical professionals.
引用
收藏
页码:74 / 86
页数:13
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