Abstract

The convergence of Artificial Intelligence (AI) and enhanced computing has revolutionized functional genomics and medical science, enabling groundbreaking advancements in disease diagnosis, treatment and personalized medicine. AI-driven approaches, particularly Machine Learning (ML) and Deep Learning (DL), facilitate the rapid analysis of genomic data, unveiling critical genetic variations linked to complex diseases. Additionally, AI-powered predictive models improve drug discovery, biomarker identification and targeted therapeutic interventions. This investigation explores innovative methodologies integrating AI and computational techniques to enhance genomic research, focusing on their impact on clinical decision-making and translational medicine. Moreover, it discusses the ethical considerations and challenges in deploying AI-driven solutions in genomic medicine, including data privacy, algorithmic bias and interpretability. By leveraging AI and advanced computing frameworks, functional genomics can achieve unprecedented precision in disease modeling and therapeutic development. This research investigation study aims to provide a comprehensive analysis of emerging AI-powered innovations in functional genomics, paving the way for future advancements in personalized healthcare and precision medicine.

Keywords:Artificial Intelligence (AI); Biomedical Engineering (BME); Bioinformatics; Biomedical instrumentation measurements and design; Biomedical image processing; Deep Learning (DL); Functional genomics; Machine Learning (ML); Medical informatics