clinical-nlp

Local-first healthcare AI: clinical NER and HIPAA PII de-identification on hardware you control. 2,200+ medical models, 35 model-backed PII languages, and Python, MLX, Android and browser runtimes. Apache-2.0 SDK.

Library for clinical NLP with spaCy.

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

A novel medical large language model family with 13/70B parameters, which have SOTA performances on various medical tasks

Open-source multimodal dataset: 98K+ clinical cases & 139K+ medical images from PubMed Central

Clinical XLNet: Modeling Sequential Clinical Notes and Predicting Prolonged Mechanical Ventilation

[ACL 2024 Findings] This is the code for our paper "Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models".

Fact Verification for Clinical Notes with LLMs

Multitask Learning with Pretrained Transformers

[NeurIPS 2022] Code for "Retrieve, Reason, and Refine: Generating Accurate and Faithful Discharge/Patient Instructions"

Discovering Related Clinical Concepts using Large Amounts of Clinical Notes. An unsupervised graphical approach to mine related concepts by leveraging the volume within large amounts of clinical notes.

Adapting Qwen2.5-14B to Brazilian SUS clinical guidelines. Includes 2 open benchmarks (HealthBench-BR, PCDT-QA) and 8 model checkpoints from the paper's ablations.

The project is in the incubation stage and still under development. ForteHealth is a flexible and powerful ML workflow builder for biomedical and clinical scenarios. This is part of the CASL project: http://casl-project.ai/

Instructions and code to create for a table of UMLS, SNOMED or HPO concepts containing Dutch medical names, usable in named entity recognition and linking methods such MedCAT.

Dilated Convolutional Attention Network for Medical Code Assignment from Clinical Text, ClinicalNLP workshop at EMNLP 2020

A rule-based Python module for spitting documents into sections.

Evidence-synthesis RAG assistant for TCM practitioners — hybrid vector + knowledge graph retrieval over 17 classical texts, with query classification, self-critique verification, and blind A/B arena evaluation.

⭐ Awesome Medical QA/RAG: A curated collection of 250+ papers, datasets, and benchmarks for Healthcare AI, Medical RAG, Knowledge Graphs, Clinical LLMs, and Multilingual Reasoning.

基于自然语言处理的智能医疗诊断系统

Explainable clinical reasoning engine combining Graph Attention Networks (GAT), BioBERT embeddings, and Neo4j knowledge graphs for disease prediction and dietary contraindications.