Revolutionizing Healthcare Management with AI driven Genomic Analysis: A Machine Learning and Cloud Computing Approach to Precision Medicine and Population Health Monitoring

Abstract

Artificial Intelligence (AI)-driven genomic analysis is transforming healthcare management by enabling precision medicine and 
large-scale population health monitoring. This study explores the integration of Machine Learning (ML) and cloud computing to 
analyze genomic data, predict disease risks, and personalize treatment strategies. ML algorithms enhance genomic sequencing by 
identifying genetic markers, uncovering complex patterns, and improving diagnostic accuracy. Cloud computing facilitates secure, 
scalable, and real-time data sharing, allowing healthcare providers and researchers to collaborate on global genomic datasets while 
ensuring data privacy and compliance. Additionally, AI-powered genomic insights contribute to early disease detection, targeted 
therapies, and public health interventions. This research highlights the benefits, challenges, and ethical considerations of AI-driven 
genomic analysis, emphasizing its role in revolutionizing precision medicine, optimizing healthcare workflows, and improving 
patient outcomes in an increasingly data-driven medical ecosystem.