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This paper reviews the application of artificial intelligence (AI) and machine learning (ML) in precision medicine, focusing on how these technologies integrate patient genomics, lifestyle data, and clinical records to personalize care. The review synthesizes evidence from randomized controlled trials, systematic reviews, and large-scale implementations, highlighting AI's potential to transform patient care through data-driven precision. It also addresses critical data security and ethical considerations associated with AI in healthcare.
AI and ML hold promise for personalized medicine through improved diagnostics, biomarker discovery, and tailored therapeutics, but require robust security and ethical frameworks.
The development of artificial intelligence (AI) and machine learning (ML) has become a new disruptive technology in precision medicine, which allows the provision of tailored treatment plans with the help of sophisticated data analytics, multimodal assimilation, and predictive modelling. It is an empirical review of the recent literature on AI and ML in the context of precision medicine, specifically how they can be used to combine patient genomics, lifestyle data, and clinical records to provide personalised care delivery. The review covers the new advances in genomics, clinical diagnostics, biomarker discovery, personalised therapeutics, and answers questions on the issues of critical data security in healthcare and ethical concerns. Randomised controlled trials, systematic reviews, and massive implementations provide evidence indicating that AI can transform patient care by means of precision based on data, but show that stringent security systems and ethics governance are needed.
