ALGORITHMS FOR INTELLIGENT MONITORING OF THE CONDITION OF PATIENTS WITH HEART DISEASE
Keywords:
Artificial intelligence, Internet of Things, Machine learning, Data Integration, Predictive Modeling.Abstract
Algorithms for Intelligent Monitoring of the Condition of Patients with Heart Disease represent a transformative approach in healthcare. This article delves into their significance, challenges, and implications. They enable early detection, personalized care, and data-driven decision-making, ultimately improving patient outcomes. However, ethical considerations and health equity are essential. These algorithms are shaping the future of cardiac care, moving us closer to a world where heart disease can be effectively managed with precision and compassion, benefiting patients worldwide.
References
Ahmed Al Ahdal, Manik Rakhra, Rahul R. Rajendran, Farrukh Arslan, Moaiad Ahmad Khder. Monitoring Cardiovascular Problems in Heart Patients Using Machine Learning, Journal of Healthcare Engineering Volume 2023, Article ID 9738123, 15 pages.
N.Raximov, O.Primqulov, B.Daminova. Basic concepts and stages of research development on artificial intelligence // International Conference on Information Science and Communications Technologies: Applications, Trends and Opportunities http://www.icisct2021.org/ ICISCT 2021, November 3-5, 2021.
N.Raximov, J.Quvondikov, X.Dusanov, B.Daminova. As a mechanism that achieves the goal of decision management // International Conference on Information Science and Communications Technologies: Applications, Trends and Opportunities http://www.icisct2021.org/ ICISCT 2021, November 3-5, 2021.
N.Raximov, M.Doshchanova, O.Primqulov, J.Quvondikov. Development of architecture of intellectual information system supporting decision-making for health of sportsmen // 2022 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA), 2021, September 6, 2022.
Kamilov M.M., Khujaev OK, Egamberdiev NA The method of applying the algorithm of calculating grades for finding similar diagnostics in medical information systems, International Journal of Innovative Technology and Exploring Engineering, 8-6S, pp. 722-724.
Muhamediyeva DT, Jurayev Z.Sh., Egamberdiyev NA, Qualitative analysis of mathematical models based on Z-number // Proceedings of the Joint International Conference STEMM: Science – Technology – Education – Mathematics – Medicine. May 16-17, 2019, Tashkent, pp. 42-43.
NAEgamberdiev, OTXolmuminov, Khrochilov, CHOOSING AN EFFICIENT ALGORITHM FOR SOLVING THE CLASSIFICATION PROBLEM, International Scientific Online Conference: THEORETICAL ASPECTS IN THE FORMATION OF PEDAGOGICAL SCIENCES, October 10, 2022, pp.154-158.
D. Muhamediyeva, N. Egamberdiyev, An application of Gauss neutrosophic numbers in medical diagnosis, International Conference on Information Science and Communications Technologies ICISCT 2021, Tashkent, Uzbekistan, 2021, pp. 1-4.