medical-informatics 开源项目推荐（306 个）

openemr /openemr

最受欢迎的开源电子健康记录与医疗实践管理解决方案。

albarqouni /Deep-Learning-for-Medical-Applications

Deep Learning Papers on Medical Image Analysis

HospitalRun /hospitalrun

Monorepo that holds all of HospitalRun's v2 projects.

dicoogle /dicoogle

Dicoogle - 开源 PACS

caufieldjh /awesome-bioie

🧫 A curated list of resources relevant to doing Biomedical Information Extraction (including BioNLP)

abachaa /MedQuAD

Medical Question Answering Dataset of 47,457 QA pairs created from 12 NIH websites

Georgetown-IR-Lab /QuickUMLS

System for Medical Concept Extraction and Linking

abachaa /Existing-Medical-QA-Datasets

Multimodal Question Answering in the Medical Domain: A summary of Existing Datasets and Systems

medmcqa /medmcqa

A large-scale (194k), Multiple-Choice Question Answering (MCQA) dataset designed to address realworld medical entrance exam questions.

mlcommons /GaNDLF

一个通用的应用程序框架，用于使用PyTorch进行分割、回归和分类

yuhaozhang /summarize-radiology-findings

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

RSNA /anonymizer

RSNA DICOM Anonymizer

AdaptInfer /Contextualized

An SKLearn-style toolbox for estimating and analyzing models, distributions, and functions with context-specific parameters.

zonghui0228 /BioMedical-NLP-corpus

Biomedical NLP Corpus or Datasets.

VectorInstitute /odyssey

患者临床时间线的可解释基础模型：事件预测、校准的至事件时间警报、概念级可解释性，并通过 MEDS 标准在 MIMIC-IV、eICU 和 GEMINI 上与调优 GBM、表格基础模型和生存基线进行正面对比基准测试。

mjpyeon /pytorch-dicom-classification

Code for analyzing medical images saved as .dicom files

cair /TextUnderstandingTsetlinMachine

Using the Tsetlin Machine to learn human-interpretable rules for high-accuracy text categorization with medical applications

bachlab /PsPM

Precision psychophysiology made easy

fhirpack /fhirpack

FHIR Python Analysis Client and Kit (FHIRPACK) is a general purpose FHIR client that simplifies the access, analysis and representation of FHIR and EHR data using PANDAS, an ETL philosophy and a functional syntax. It was initially developed at the IKIM and HDDBS in Germany. Read more at https://zenodo.org/record/8006589

JZK00 /Radiomics-research-by-using-Python

Radiomics (here mainly means hand-crafted based radiomics) contains data acquire, ROI segmentation, feature extraction, feature selection, machine learning modeling, and stastical analysis.