Integrating multiomics approaches with AI and machine learning is transforming disease detection and prognosis. Studies include a plasma synuclein test offering sensitive Parkinson’s diagnosis, machine learning models predicting nasopharyngeal carcinoma response to radiotherapy, and AI-based identification of kidney disease types via retinal imaging. Additionally, neonatal care benefits from Bayesian algorithms predicting CO2 retention and advanced retinal scanning techniques, signaling a growing role of computational tools in personalized medicine and critical care.