The Role of Genetics in Personalized Medicine: A Comprehensive Review of IEEE Research Papers on AI-Driven Genomic Analysis and Pharmacogenomics

Personalized medicine represents a paradigm shift from the conventional “one-size- fits-all” healthcare model to an approach that tailors medical interventions based on an individual patient’s genetic composition, molecular profile, and clinical data. The inte- gration of genetics and genomics into clinical practice has enabled more precise diagnos- tics, optimized therapeutic strategies, and improved patient outcomes. This research paper presents a comprehensive review of eight peer-reviewed IEEE research papers that explore various facets of genetics in personalized medicine, ranging from artificial intelligence ap- plications in genomic analysis to pharmacogenomics and drug response prediction. The paper systematically analyzes each study’s methodology, key contributions, and clinical implications. Furthermore, we propose a unified framework for integrating AI-driven ge- nomic analysis into clinical workflows. The findings demonstrate that machine learning, deep learning, and biosimulation techniques significantly enhance the accuracy of genetic variant detection, drug sensitivity prediction, and cancer therapy optimization. This review concludes that the convergence of genetics, artificial intelligence, and multi-omics data holds transformative potential for advancing precision healthcare.