Integrating Artificial Intelligence in Precision Medicine: Enhancing Predictive Accuracy and Personalized Care in Chronic Disease Management

Authors

  • Muhammad Abdullah University of Management and Technology, Lahore

Keywords:

Chronic, Artificial intelligence, Deep Learning, Medicine, Chronic Disease Management

Abstract

This review examines the transformative potential of artificial intelligence (AI) in precision medicine, particularly within the context of chronic disease management. As chronic conditions, including cardiovascular diseases, diabetes, and cancer, remain the leading causes of mortality worldwide, there is an increasing need for innovative, individualized approaches to improve treatment outcomes. AI technologies—such as machine learning (ML), deep learning (DL), and natural language processing (NLP)—have been shown to enhance predictive accuracy, support real-time patient monitoring, and enable personalized care plans based on vast datasets and individual health profiles. This review synthesizes recent advancements in AI applications for predictive modeling, genomics, and patient-centered care in chronic disease, critically analyzing the benefits and challenges of AI integration. Ethical considerations surrounding data privacy and algorithmic bias are also discussed. The review concludes by identifying potential pathways for AI in enhancing precision medicine’s role in managing chronic disease and highlighting the need for regulatory frameworks and cross-disciplinary collaboration to overcome current limitations.

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Published

2024-06-23

How to Cite

Abdullah, M. (2024). Integrating Artificial Intelligence in Precision Medicine: Enhancing Predictive Accuracy and Personalized Care in Chronic Disease Management . Medical and Life Sciences, 3(1), 6–15. Retrieved from https://journals.smarcons.com/index.php/mls/article/view/366

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Section

Articles