# AI-in-Health/MedLLMsPracticalGuide

[Nature Reviews Bioengineering🔥] Application of Large Language Models in Medicine.  A curated list of practical guide resources of Medical LLMs (Medical LLMs Tree, Tables, and Papers)

Repository: https://github.com/AI-in-Health/MedLLMsPracticalGuide
Canonical: https://ross.abutalabs.com/products/medllmspracticalguide
Homepage: https://arxiv.org/abs/2311.05112
License: MIT
License Family: permissive
Topics: ai-in-medicine, clinical-ai, large-language-models, survey, medical-large-language-models
Last push: 2026-07-10T16:26:08+00:00

## Health v2 (maintenance only)
Score: 68/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 91, release rhythm 35, longevity 73
- inputs: {"age_days": 1030, "days_push": 54, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2041, forks 177 (observed 2026-08-28T04:06:08.414020+00:00)

## What it is
A curated, actively updated list of resources for Medical Large Language Models, accompanying a survey paper published in Nature Reviews Bioengineering. It organizes papers, tables, and a taxonomy tree covering the development, deployment, and challenges of LLMs in medicine.

## Use cases
- find papers on medical large language models
- learn how LLMs are applied in healthcare
- survey medical LLM architectures and training data
- compare LLM performance on clinical tasks
- research resources for building a medical chatbot
- keep up with new medical AI research

## When to choose
- you need a curated starting point for medical LLM research
- you want a structured taxonomy of medical LLM papers and models
- you are writing a survey or literature review on AI in medicine

## When to avoid
- you need runnable software or code for medical LLMs
- you want a production clinical AI system rather than references
- you need non-LLM medical imaging or diagnostics tools

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, developer-tools
- domain: large-language-models, healthcare, artificial-intelligence, awesome-lists, tutorials
- platform: cross-platform
- tags: awesome-list, medical-llms, survey-paper, curated-resources, clinical-ai, ai-in-medicine

## Member repositories
- AI-in-Health/MedLLMsPracticalGuide (main) score 68

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:08.414020+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:58:19.211757+00:00, confidence not recorded.
  - readme: https://github.com/AI-in-Health/MedLLMsPracticalGuide (fetched 2026-08-28T04:06:08.414020+00:00, sha 64b51f6b876c)
  - homepage: https://arxiv.org/abs/2311.05112 (fetched 2026-08-29T10:38:46.952720+00:00, sha 946b360319e3)
  - site_page: https://info.arxiv.org/about/donate.html (fetched 2026-08-29T10:38:46.962131+00:00, sha cca9c3a11c56)
  - site_page: https://info.arxiv.org/about/ourmembers.html (fetched 2026-08-29T10:38:46.965543+00:00, sha 47cbc55ff1de)
  - site_page: https://info.arxiv.org/about (fetched 2026-08-29T10:38:46.967315+00:00, sha a1f16f915a9a)
  - site_page: https://info.arxiv.org/labs/index.html (fetched 2026-08-29T10:38:46.964008+00:00, sha b14a8d05a0ec)
- Data as of 2026-08-30T08:39:29.467469+00:00.