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In our Interviews with Innovators, we talked with Barry Canton from Gingko Bioworks about using large language models (LLMs) in bioengineering. It’s a fascinating read:

Creating large language model that "speaks DNA"

Interview with Barry Canton from Gingko Bioworks about real-life implementation of ML and AI

www.turingpost.com/p/barrycanton-gingko

Inspired by this interview, we compiled a list of medical LLMs. The field of medicine is one of the crucial and rapidly advancing areas for the application of LLMs. We hope you’ll find this list helpful.

LLaMA-based models

  • MEDITRON-70B: Built on Llama-2, pretrained on a medical corpus, achieving high performance on medical benchmarks. Paper, code

  • PMC-LLaMA: Adapted LLaMA using PubMed articles, significantly improving performance on medical benchmarks. Paper, code

  • Clinical Camel: Fine-tuned from LLaMA-2, utilizes QLoRA and dialogue-based knowledge encoding for superior performance on medical benchmarks. Paper

  • ChatDoctor: Fine-tuned from LLaMA, using 100,000 patient-doctor dialogues to enhance diagnostic accuracy. Paper, code

  • Radiology-Llama2: Specialized in radiology, trained on extensive radiology datasets, excelling in generating clinically useful impressions. Paper

  • Hippocrates: An open-source framework for developing medical LLMs, with models fine-tuned from Mistral and LLaMA 2. Paper, blog post

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