AI in precision medicine is considering a major turning point in health care toward personalized treatments per each one's profile, hence playing an important role in patient outcomes while affecting the bottom line in healthcare. This paper examines the economic implications of AI- driven precision medicine, including how the use of AI tools-such as machine learning and predictive analytics-will add to developing treatments tailored to a particular patient's genetics, medical history, and current health data. The study presented underlined economies that could be obtained by avoiding superfluous treatments, reduction in hospital readmission rates, and adverse drug reactions by analyzing the tendencies in healthcare spending. Further, AI enhances the overall efficiency of the health system through speeding up drug development, smoothing clinical processes, and raising the quality of decision-making on patient care. Notwithstanding the brilliant prospects, general acceptance of AI in healthcare systems might be prospective due to high implementation costs, data privacy concerns, and regulatory hurdles. Done differently, AI-driven precision medicine can significantly enhance patient care while lowering long-term healthcare costs. But complete global realization of this dream requires resolution of ethical, financial, and operational challenges.
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- et al. (2024) studied this question.
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