التفاصيل البيبلوغرافية
| العنوان: |
Machine learning based prediction model for acute coronary syndrome using biomarker. |
| المؤلفون: |
Hajare, Shital1 (AUTHOR) svanjankar@gmail.com, Rewatkar, Rajendra1 (AUTHOR) rajendrar.feat@dmiher.edu.in, Reddy, K. T. V.1 (AUTHOR) ktvreddy.feat@dmiher.edu.in |
| المصدر: |
AIP Conference Proceedings. 2024, Vol. 3188 Issue 1, p1-6. 6p. |
| مصطلحات موضوعية: |
*ACUTE coronary syndrome, *CORONARY disease, *FEATURE selection, *ARTIFICIAL intelligence, *HEART diseases |
| مستخلص: |
Cardio-vascular diseases, particularly acute coronary disease, remain a leading cause of mortality worldwide. Timely and accurate prediction of heart disease risk is essential for effective prevention and intervention strategies. In recent years, the integration of artificial intelligence (AI) and biomarkers has emerged as a promising approach to enhance heart disease prediction accuracy. This paper provides a comprehensive review of the role of biomarkers in heart disease prediction utilizing AI techniques. Subsequently, the paper explores the integration of AI methodologies, such as machine learning in analyzing complex biomarker data. AI-driven algorithms have demonstrated the capability to identify intricate patterns and relationships within vast datasets, thereby enabling the development of accurate predictive models. Training, validation, and interpretability of the feature selection model are crucial for heart disease prediction. The proposed method offers a precise prediction model to identify heart-related problems, such as the fusion of biomarkers and AI technologies presents a game-changing opportunity to advance heart disease prediction and prevention strategies. Collaboration between clinicians, researchers, and AI specialists is crucial as the field develops in order to realize the full potential of these strategies and enhance cardiovascular health globally, diagnosis, treatment plan, and risk of complications. [ABSTRACT FROM AUTHOR] |
| قاعدة البيانات: |
Academic Search Index |