Healthcare
Overview
Healthcare AI uses patient records, medical images, signals, and conversations to support tasks such as diagnosis, risk prediction, treatment planning, and care coordination. Common approaches include supervised learning, multimodal foundation models, retrieval-augmented generation, knowledge graphs, and reinforcement learning. Systems are tested on resources such as MIMIC-IV, MedQA, and CheXpert, as well as through clinician studies and workflow evaluations. A central challenge is that strong benchmark results do not guarantee safe, fair, reliable performance with incomplete information, changing clinical settings, or real patients, so prospective validation and careful governance remain essential.
Latest papers
621 papers24 papers in the last four weeks, down 40% on the four weeks before. 0.1% of all new papers.