$ show richard-peng-xia/awesome-multimodal-in-medical-imaging
This repository is a curated 'awesome list' of research resources on multimodal learning in medical imaging. It contains no application code, tests, or data pipelines; its sole substantive file is a large README.md that catalogs papers, datasets, benchmarks, and code repositories. Topics span medical vision-language models, report generation, visual question answering, retrieval-augmented generation (RAG), and multimodal LLMs. The list is organized by task and includes links to arXiv PDFs, GitHub code, and dataset sources, with badges indicating publication venues.
The LLM identified 1 files worth highlighting for reuse:
The repository's sole content file, a comprehensive markdown index of multimodal medical imaging research. It organizes papers by task (report generation, VQA, vision-language models, RAG), provides links to PDFs and code, and includes dataset tables. Reusable as a template for building domain-specific awesome lists; demonstrates systematic curation with consistent formatting and contribution guidelines.