… medical AI systems utilize unstructured EHRs. In this study, we develop from scratch a large
clinical language model… -identified clinical text) and systematically evaluate it on five clinical …

… medical AI systems utilize unstructured EHRs. In this study, we develop from scratch a large
clinical language model … de-identified clinical text) and systematically evaluate it on 5 clinical …

… ChatGPT is a large language model (LLM), a type of FM which ingests text and outputs text
in response. Though ChatGPT was trained to simply predict the next word in a sentence—it is …

… , similar to the masked language model objectives introduced in … The pre-trained language
model was then used to initialise the … of hyperparameters of the language model, such as the …

… large volumes of unstructured medical data. In this paper, we present MedRoBERTa.nl, the
first language model trained on Dutch hospital … takers in hospitals about an individual patient. …

… electronic health records of a local hospital. We annotated named entities in 200 pathology
reports and 50 clinical … We kept pretraining the BlueBERT model on the cancer corpus with …

… Like BLEU and ROUGE, CIDEr is based on an n-gram language model, and so we modify
it to allow for variable-length n-grams to avoid producing harsh ratings for synthetic chief …

… For LLM-related keywords, we used two general terms, “large language model” and “LLM,” …
two search terms, “Electronic Medical Record” and “Electronic Health Record.” We applied …

… missing or incomplete in the structured data of electronic health records (EHRs). Large language
models (LLMs) could … LLM large language model, SDoH Social determinants of health. …

… information extraction model based on a state-of-the-art large language model, a GPT-2
generative model that can extract headache frequency from EHR free-text clinical notes with …