Abstract
As genomic research becomes more complex and data-rich, artificial intelligence (AI) has emerged as a crucial tool for processing and analyzing high-dimensional genomic data, accelerating biomarker discovery, and enhancing genomic sequence annotations. Despite the increasing application of AI in genomic research, challenges persist, particularly regarding the integration of biomedical knowledge into algorithm development. We reviewed high-quality, AI-driven biomedical genomic studies from the past five years, covering applications in disease prediction, detection, diagnosis, and treatment. Each category highlights how different AI techniques are applied in biomedical contexts. Furthermore, we identify current challenges and potential solutions in AI-assisted biomedical genomics. This comprehensive review is designed to encourage collaboration among computer scientists, healthcare professionals, and interested communities, propelling the development of AI applications that can be smoothly integrated into routine medical services.
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