Clinical text datasets for medical artificial intelligence and large language models—a systematic review

Privacy and ethical considerations limit access to large-scale clinical datasets, particularly clinical text data, which contain extensive and diverse information and serve as the foundation for building clinical large language models (LLMs). The limited accessibility of clinical text data impedes the development of clinical artificial intelligence systems and hampers research participation from resource-poor regions and medical institutions, thereby exacerbating health care disparities. In this review, we conduct a global review to identify publicly available clinical text datasets and elaborate on their accessibility, diversity, and usability for clinical LLMs. We screened 3962 papers across medical (PubMed and MEDLINE) and computational linguistic academic databases (the Association for Computational Linguistics Anthology) as well as 239 tasks from prevalent medical natural language processing (NLP) challenges, such …