Bridging Artificial Intelligence and Healthcare: A Data-Driven Approach to Precision Medicine
Abstract
The integration of artificial intelligence (AI) into healthcare has the potential to revolutionize patient treatment through precision medicine. This study explores machine learning algorithms for disease prediction, diagnosis, and personalized treatment planning based on patient data. By leveraging large-scale medical datasets, AI-driven models can identify patterns that enhance early disease detection and optimize treatment regimens. The paper presents a case study on AI applications in oncology, demonstrating improved accuracy in cancer diagnosis. The findings highlight the challenges of data privacy, algorithmic bias, and clinical adoption while providing insights into future research directions in AI-powered healthcare.
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