Data driven strategies to combat chronic diseases globally
1 Faculty of Health and Life Sciences, De Montfort University, Leicester, United Kingdom.
2 Brandeis International Business School, Brandeis University, Waltham, USA.
Review Article
GSC Advanced Research and Reviews, 2024, 21(03), 235–240.
Article DOI: 10.30574/gscarr.2024.21.3.0491
Publication history:
Received on 31 October 2024; revised on 11 December 2024; accepted on 13 December 2024
Abstract:
Globally, chronic diseases such as diabetes, cardiovascular disease, and cancer pose major public health challenges and are the leading causes of mortality and morbidity. These diseases strain health care systems and economies due to the long-term care they require. This paper explores the potential of data-driven strategies to enhance the management of chronic diseases on a global scale. Through the application of big data analytics, machine learning, and predictive modeling, there are significant opportunities to improve prevention, management, and treatment outcomes. The integration of these technologies allows for real-time health monitoring and personalized medicine, which could substantially reduce the overall impact of chronic diseases.
Keywords:
Predictive Analytics; Machine Learning; Chronic Disease Management; Healthcare Data Security; Personalized Medicine
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0
