Artificial intelligence and machine learning steadily permeate medical diagnostics and treatment innovation. The AI model PromoterAI accurately identifies promoter mutations that dysregulate gene expression, addressing a critical gap in rare genetic disease variant interpretation. Additionally, hybrid multi-instance learning incorporating Transformers and graph attention networks achieves high accuracy in classifying gastric adenocarcinoma differentiation from pathology images. AI applications optimize sleep diagnostics as demonstrated by EnsoData’s $20 million funding for their sleep disorder platform. These developments exemplify AI’s growing role in precision diagnostics and personalized patient care.