datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
medicine-tasks
Adapting LLMs to Domains via Continual Pre-Training (ICLR 2024)
This repo contains the evaluation datasets for our paper Adapting Large Language Models via Reading Comprehension.
We explore continued pre-training on domain-specific corpora for large language models. While this approach enriches LLMs with domain knowledge, it significantly hurts their prompting ability for question answering. Inspired by human learning via reading comprehension, we propose a simple method to… See the full description on the dataset page: https://huggingface.co/datasets/AdaptLLM/medicine-tasks.IndustryInstruction_Health-Medicine
IndustryInstruction: Health & Medicine
This repository contains the IndustryInstruction: Health & Medicine domain subset of BAAI/IndustryInstruction.
Refer to the parent dataset card for data construction, intended use, limitations,
and licensing details.
Citation
If you use this dataset in your work, please cite IndustryInstruction:
@misc{shi2024industryinstruction,
title = {IndustryInstruction},
author = {Xiaofeng Shi and Lulu Zhao and Hua Zhou and… See the full description on the dataset page: https://huggingface.co/datasets/BAAI/IndustryInstruction_Health-Medicine.turkish-medicine-law
turkish-medicine-law
Bu veri seti, Türkçe tıp ve sağlık hukuku alanında hazırlanmıştır. Türkçe hukuk alanında genel amaçlı birkaç kaynak bulunuyor, ama tıp hukuku özelinde hazırlanmış bir veri seti şimdiye kadar yoktu. Bu proje o boşluğu doldurmayı amaçlıyor.
Veri setindeki örnekler hukukçular, bilirkişiler ve sağlık kuruluşlarının hukuk birimleri için hazırlandı. Hastaya veya hekime doğrudan hukuki görüş sunmak amacıyla kullanılmak üzere tasarlanmadı. Buradaki çıktılar bir ön… See the full description on the dataset page: https://huggingface.co/datasets/tunahanf/turkish-medicine-law.IndustryCorpus_medicine[中文主页]
Industry models play a crucial role in driving enterprise intelligence transformation and innovative development. High-quality industry data is key to improving the performance of large models and realizing industry applications. However, datasets currently used for industry model training generally suffer from issues such as insufficient data volume, low quality, and lack of domain expertise.
To address these problems, we constructed and applied 22 industry data processing operators to… See the full description on the dataset page: https://huggingface.co/datasets/BAAI/IndustryCorpus_medicine.korean-medicine-embedding-dataset
Korean Medicine Embedding Dataset (한의학 임베딩 데이터셋)
A contrastive-learning dataset for training and evaluating domain-adapted text embedding models for Korean Medicine (KM, 한의학). Each example is a query–positive–negatives triplet built from KM terminology resources and a curated KM ontology, capturing semantic relations such as disease–symptom, disease–prescription, prescription–indication, prescription–herb, and herb–indication.
This dataset accompanies the study "A Domain-Adapted… See the full description on the dataset page: https://huggingface.co/datasets/cnupo23/korean-medicine-embedding-dataset.CMMLU-Traditional-Chinese-Medicine-Benchmark
💻 Dataset Usage
Run the following command to load the testing set (185 examples):
from datasets import load_dataset
dataset = load_dataset("shuyuej/CMMLU-Traditional-Chinese-Medicine-Benchmark", split="train")
print(dataset)
CMMLU-College-Medicine-Benchmark
💻 Dataset Usage
Run the following command to load the testing set (237 examples):
from datasets import load_dataset
dataset = load_dataset("shuyuej/CMMLU-College-Medicine-Benchmark", split="train")
print(dataset)
tw-emergency-medicine-bench
Dataset Card for tw-emergency-medicine-bench
tw-emergency-medicine-bench 是一個以台灣衛生福利部急診醫學科專科醫師甄審筆試為基礎之繁體中文醫學評測資料集，包含 1,719 題選擇題。資料採 Formosa-bench 評測集之欄位格式（question / A / B / C / D / E / answer），可直接用於語言模型之 zero-shot 或 few-shot 多選題評測。
Dataset Details
Dataset Description
本資料集源自台灣衛生福利部所辦理之「急診醫學科專科醫師甄審筆試試題」公開題庫。每題由臨床情境描述（症狀、病史、理學檢查、實驗室數值等）與選項組成，並附帶標準答案。題目同時包含 4 選項（A–D）與 5 選項（A–E）兩種題型：
選項數
題數
5 選項（A–E）
999
4 選項（A–D）
720
為對齊 Formosa-bench… See the full description on the dataset page: https://huggingface.co/datasets/lianghsun/tw-emergency-medicine-bench.Traditional-Chinese-Medicine-Knowledgeindonesian-traditional-medicine
Indonesian Traditional Medicine Q&A Dataset
Dataset pengetahuan pengobatan tradisional Indonesia untuk training model bahasa.
Deskripsi
Dataset ini berisi pasangan tanya-jawab tentang pengobatan tradisional, tanaman obat, jamu, dan etnomedisin Indonesia dalam Bahasa Indonesia. Dirancang untuk melatih model bahasa agar memahami dasar-dasar pengobatan tradisional Nusantara.
Dataset ini disediakan oleh KLINEXA — penyedia model LLM khusus kesehatan Indonesia.… See the full description on the dataset page: https://huggingface.co/datasets/emylton/indonesian-traditional-medicine.mmlu-professional-medicineFrench-MMLU-Professional-Medicine-Benchmark
💻 Dataset Usage
Run the following command to load the testing set:
from datasets import load_dataset
dataset = load_dataset("shuyuej/French-MMLU-Professional-Medicine-Benchmark", split="test")
print(dataset)
indonesian_disease_medicine_icd
Indonesian Disease, Medicine & ICD-10 Q&A Dataset
Dataset penyakit, pengobatan, dan kode ICD-10 untuk training model bahasa kesehatan Indonesia.
Deskripsi
Dataset ini berisi pasangan tanya-jawab tentang penyakit umum di Indonesia, kode ICD-10, pengobatan standar, dan obat-obatan dalam Bahasa Indonesia. Setiap jawaban mencakup:
Kode ICD-10 lengkap dengan subkategori
Gejala klinis utama
Pengobatan standar (farmakologi & non-farmakologi)
Nama obat spesifik beserta dosis… See the full description on the dataset page: https://huggingface.co/datasets/emylton/indonesian_disease_medicine_icd.medicine-informationFrench-MMLU-College-Medicine-Benchmark
💻 Dataset Usage
Run the following command to load the testing set:
from datasets import load_dataset
dataset = load_dataset("shuyuej/French-MMLU-College-Medicine-Benchmark", split="test")
print(dataset)
camel_loong_medicine
Additional Information
This dataset contains mathematical problem-solving traces generated using the CAMEL framework. Each entry includes:
A mathematical problem statement
A detailed step-by-step solution
medicine_dataset
Additional Information
This dataset contains medicine problems generated using the CAMEL framework. Each entry includes:
A question
A detailed rationale explaining the solution approach
The llm_answer
medicineSpanish-MMLU-Professional-Medicine-Benchmark
💻 Dataset Usage
Run the following command to load the testing set:
from datasets import load_dataset
dataset = load_dataset("shuyuej/Spanish-MMLU-Professional-Medicine-Benchmark", split="test")
print(dataset)
camel_loong_medicine_medcal_train30
Additional Information
This dataset contains mathematical problem-solving traces generated using the CAMEL framework. Each entry includes:
A mathematical problem statement
A detailed step-by-step solution
RLT-medicine_biology-expert-17kmedicine-infommlu-college-medicineMedicine_DetailsThis dataset is derived and revised from MattBastar/medicine.
lora_medicinemedicine-data-rawschemaforge-ai-in-health-and-medicine-14
www.statnews.com
Auto-refined by SchemaForge
Metadata
Topic: AI in Health and Medicine
Quality Score: 0.92
Source: Autonomous web scraper
Extracted Facts
STAT covers AI use in health care and medical science
AI may diminish physician autonomy
Federal regulators hold closed-door meetings on clinical AI
Schrödinger CEO Ramy Farid changed his approach to AI
Federation of State Medical Boards licenses AI to practice medicine
AI scribes are useful… See the full description on the dataset page: https://huggingface.co/datasets/GudduButt/schemaforge-ai-in-health-and-medicine-14.phyto-plant-medicinemedicine_testHindi-MMLU-Professional-Medicine-Benchmark
💻 Dataset Usage
Run the following command to load the testing set (272 examples):
from datasets import load_dataset
dataset = load_dataset("shuyuej/Hindi-MMLU-Professional-Medicine-Benchmark", split="test")
print(dataset)