LLYXC

Awesome-Foundation-Models-for-Advancing-Healthcare

We present a comprehensive and deep review of the HFM in challenges, opportunities, and future directions. The released paper: https://arxiv.org/abs/2404.03264

MICA

Implementation of the paper MICA.

ICMIL

Iteratively Coupled Multiple Instance Learning

BenchMD

ScienceQA

Data and code for NeurIPS 2022 Paper "Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering".

FedLSM

CheXzero

This repository contains code to train a self-supervised learning model on chest X-ray images that lack explicit annotations and evaluate this model's performance on pathology-classification tasks.

RadFM

The official code for "Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Data".

ViT-Adapter

[ICLR 2023 Spotlight] Vision Transformer Adapter for Dense Predictions

unilm

Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

UnblockNetEaseMusic

自动化绕过网易云海外限制

shap

A game theoretic approach to explain the output of any machine learning model.

CRATE

Code for CRATE (Coding RAte reduction TransformEr).

IRENE

MedSAM

Segment Anything in Medical Images

MEDFAIR

[ICLR 2023 spotlight] MEDFAIR: Benchmarking Fairness for Medical Imaging

ChatDoctor

researchgpt

An open-source LLM based research assistant that allows you to have a conversation with a research paper

DebiAN

Official code of "Discover and Mitigate Unknown Biases with Debiasing Alternate Networks" (ECCV 2022)

DDAD

MICCAI 2022 (Early Accepted): Dual-Distribution Discrepancy for Anomaly Detection in Chest X-Rays

Co-teaching

NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels

LfF

Learning from Failure: Training Debiased Classifier from Biased Classifier (NeurIPS 2020)

MAPLE

Code for Model Agnostic Sample Reweighting for Out-of-Distribution Learning

nice

BR-Net

ICAM

ICAM: Interpretable Classification via Disentangled Representations and Feature Attribution Mapping

LDDG

[NIPS 2020] The code release of paper 'Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization'

bias-contrastive-learning

Official Pytorch implementation of "Unbiased Classification Through Bias-Contrastive and Bias-Balanced Learning (NeurIPS 2021)

LaCIM

Learning-Debiased-Disentangled

Official Pytorch implementation of "Learning Debiased Representation via Disentangled Feature Augmentation (Neurips 2021, Oral)"