Artificial Intelligence and Bioinformatics in Genomic Medicine: Tools, Applications, and Future Directions

This chapter surveys the transformative role of machine learning, deep learning, and advanced bioinformatic pipelines in analysing the large-scale genomic, transcriptomic, and proteomic datasets that define modern medical genetics research. It reviews algorithmic approaches to variant calling and prioritisation, AI-assisted radiogenomics, and the application of natural language processing to the clinical genetics literature. The chapter also addresses the challenges of algorithmic bias, data privacy, model interpretability, and the integration of AI tools into routine genomic workflows.