Large language models (LLMs) can respond to free-text queries without being specifically
trained in the task in question, causing excitement and concern about their use in healthcare …

Large Language Models (LLMs) went from non-existent to ubiquitous in the machine
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …

The success of foundation models such as ChatGPT and AlphaFold has spurred significant
interest in building similar models for electronic medical records (EMRs) to improve patient …

Analyzing vast textual data and summarizing key information from electronic health records
imposes a substantial burden on how clinicians allocate their time. Although large language …

Large language models (LLMs) are a special class of pretrained language models (PLMs)
obtained by scaling model size, pretraining corpus and computation. LLMs, because of their …

Large language models (LLMs) have significantly advanced the field of natural language
processing (NLP), providing a highly useful, task-agnostic foundation for a wide range of …

Sifting through vast textual data and summarizing key information from electronic health
records (EHR) imposes a substantial burden on how clinicians allocate their time. Although …

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 …

Background Both medical care and observational studies in oncology require a thorough
understanding of a patient's disease progression and treatment history, often elaborately …

The rapid progress of large language models (LLMs) driving generative artificial intelligence
applications heralds the potential of opportunities in health care. We conducted a review up …