Popular GitHub Repositories for Medicine

QiZhenGPT: An Open Source Chinese Medical Large Language Model｜一个开源的中文医疗大语言模型

A framework for creating grounded instruction based datasets and training conversational domain expert Large Language Models (LLMs).

Implementation of ChatGPT, but tailored towards primary care medicine, with the reward being able to collect patient histories in a thorough and efficient manner and come up with a reasonable differential diagnosis

The paper list of the review on LLMs in medicine - "Large Language Models Illuminate a Progressive Pathway to Artificial Healthcare Assistant: A Review".

Implementation of MedSegDiff in Pytorch - SOTA medical segmentation using DDPM and filtering of features in fourier space

TemporAI: ML-centric Toolkit for Medical Time Series

A repository to house some personal attempts to beat some state-of-the-art for medical datasets

赛博医生项目——”赛博华佗“，基于多模态大模型的多功能智能体，一键搭建本地多模态大模型。接入医疗健康相关的知识图谱和知识库后可以进行疾病初诊，病历分析，专业知识问答等功能，成为你的私人医生。赛博华佗项目能帮助实现医疗资源的跨地域传播，让更多人借助大模型改善健康水平。"Cyber ??Huatuo" - Easy to build a personal doctor agent based on LLM and Knowledge Graph/Knowledge Database.

Code and pretrained model for paper "Learning to Summarize Radiology Findings"

Self-verification for LLMs.

This repository is a summary of "AI for Medicine" lectured by Deeplearning.ai, Coursera. (https://www.coursera.org/specializations/ai-for-medicine)

The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation (NeurIPS 2021) by Alex J. Chan, Ioana Bica, Alihan Huyuk, Daniel Jarrett, and Mihaela van der Schaar.

Variational Inference of Polygenic Risk Scores

LLM Agents Making Agent Tools

行学AI，你的学术科研AI助手！学术GPT， 支持英文润色，中文润色 支持论文摘要、论文里面的细节探讨、ChatGPT3.5和ChatGPT4.0强力加持的大模型，让AI助手真正能助力学术科研人员更好的掌握学术论文

Deep learning for personalized interpretability for compositional health data

An End-to-end Machine Learning System with User Interface for predicting the 10-year risk of death of individuals from the NHANES I epidemiology dataset. This project leverages risk models (a.k.a. prognostic models) built using machine learning to perform predictions given the patient's medical profile.

Artificial Intelligence Project

Self-Supervised Learning in Medicine Review

Using DeepChem with TensorFlow 2.x and Keras