Technology: language: Large Language Model

Large Language Model for Healthcare

Large language models (LLM) utilizing pre-trained generative transformer (GPT) architecture have achieved tremendous success in natural language processing (NLP). In healthcare applications, LLMs have also demonstrated great potential in processing and analyzing medical texts, paving the way for revolutionizing the healthcare industry, aiding physicians in their daily work, and improving the quality of patient care. At CAMCA, we have conducted a wide range of research on developing, improving, and harnessing LLM solutions for healthcare applications. Some of our recent healthcare LLM projects include: 1) RadiologyGPT, a fine-tuned LLAMA2 7B model using radiology reports from a public dataset; 2) ImpressionGPT, developing exemplar-based prompt engineering for summarizing radiology reports; 3) CohortGPT: establishing patient cohort via chain-of-thought technique on LLMs; 4) DeID-GPT: leveraging LLMs for removing HIPPIA identifiers from the medical text.

Related publications:

RadiologyGPT: https://arxiv.org/abs/2309.06419

ImpressionGPT: https://arxiv.org/abs/2304.08448

CohortGPT: https://arxiv.org/abs/2307.11346

DeID-GPT: https://arxiv.org/abs/2303.11032

https://link.springer.com/chapter/10.1007/978-3-031-43075-6_34

https://arxiv.org/abs/2307.13693

https://arxiv.org/abs/2306.10095

https://arxiv.org/abs/2306.08666

https://arxiv.org/abs/2305.03513

https://arxiv.org/abs/2304.11567

https://arxiv.org/abs/2304.09138

https://arxiv.org/abs/2304.01938

https://arxiv.org/abs/2302.10447

https://arxiv.org/abs/2302.13007

https://link.springer.com/chapter/10.1007/978-3-031-21014-3_28