Artificial Intelligence in Personalized Medicine: A Survey on FuncPredict: AI Driven Genetic Variant Analysis

Personalized medicine is a new concept that transforms health care in the context of tailoring strictly towards the needs of an individual patient, using genetic, molecular, and clinical data. This new wave has been brought about by the advancement of genomics, technology, and artificial intelligence (AI). AI comes into play while analyzing massive datasets, identifying different patterns, and enabling predictive modelling for disease outcomes. Genomic medicine makes potent use of the Human Genome Project by relying on AI technologies to process and interpret enormous genetic data. AI enhances genome sequencing, thereby making it possible to be more sensitive and specific in detecting genetic variations that predispose or cause diseases. In pharmacogenomics, AI optimizes drug prescriptions based on genetic profiles to make therapies more effective and personalized. AI, particularly ML and DL, helps in the advanced genomic analysis in clinical genomics, going beyond what is allowed by the traditional bioinformatics to study genomic patterns that wouldn't have been possible under previous standards. Advanced genomic analysis paves the way for precision medicine, providing insights in terms of cancer diagnosis, optimising treatment, and prognosis by the inspection of complex genomic data including SNVs, structural variations, and CNVs. This paper briefly surveys the integration of AI in personalized medicine and genomic research; it would most likely revolutionize healthcare outcomes. As this paper surveys the following, it is apparent that including AI in personal medicine highly enhances genomic study and treatment personalization. The promise of such an advancement includes improved patient outcomes through precised diagnostics, tailored therapies, and optimized disease management strategies.