Medical Report Generation

Medical report generation studies how to create diagnostic reports and clinical notes from images, patient records, or doctor–patient conversations. Approaches include vision-language models for radiology, pathology, and other imaging; speech-to-text pipelines for SOAP notes; and systems that use templates, retrieval, structured findings, or evidence-linked reasoning to guide generation. Evaluation increasingly uses clinical measures and expert review alongside language metrics on settings such as MIMIC-CXR and IU X-Ray. A central challenge is ensuring that reports are complete and factually grounded across hospitals and modalities, since fluent text and lexical similarity do not guarantee clinical accuracy or safety.