OpenMed/MedDialog

MedDialog

A large-scale medical dialogue dataset containing ~252k patient-doctor conversation pairs for training and evaluating clinical dialogue systems.

Dataset Description

Overview

MedDialog is designed for training language models to generate medically appropriate, empathetic, and safe doctor responses given a patient query. It covers a broad range of medical topics including symptoms, diagnoses, medications, procedures, and general health questions.

Dataset Structure

Fields

Statistics

Example

Patient:

I have been experiencing severe headaches for the past week, mostly in the morning. The pain is throbbing and located on the right side of my head. I also feel nauseous sometimes. What could be causing this?

Doctor:

I understand how concerning persistent headaches can be, especially when accompanied by nausea. Based on your description of throbbing, one-sided pain with morning occurrence, this could potentially be migraines, though we'd need a proper evaluation to be sure. I'd recommend: 1. Keep a headache diary noting triggers, duration, and severity 2. Ensure you're staying hydrated and getting adequate sleep 3. Avoid known migraine triggers like bright lights or certain foods However, given the duration and severity, I strongly advise scheduling an appointment with your doctor for a proper examination.

Data Processing

This dataset was derived from ruslanmv/ai-medical-chatbot (257k raw examples) with the following processing steps:

1. 1.Field combination: Merged Description and Patient fields into patient_message
2. 2.Quality filtering: Removed examples with very short messages (<5 words patient, <10 words doctor)
3. 3.Redirect filtering: Excluded entries where the doctor response was only a referral with no content
4. 4.Truncation: Capped messages at 2,500 characters
5. 5.Split: 90/10 train/validation split with random seed 42

Usage

Loading with datasets

from datasets import load_dataset

ds = load_dataset("OpenMed/MedDialog")
train = ds["train"]
val = ds["validation"]

print(train[0]["patient_message"])
print(train[0]["doctor_response"])

With Prime Intellect RL Environment

This dataset is used by the maziyar/OpenMed_MedDialog RL environment for training models via reinforcement learning with the following reward components:

prime env install maziyar/OpenMed_MedDialog

License

This dataset is released under the Apache License 2.0, inherited from the source dataset ruslanmv/ai-medical-chatbot.

Limitations and Ethical Considerations

• —This dataset is intended for research purposes only and should not be used as a substitute for professional medical advice
• —Doctor responses in the source data vary in quality and may contain inaccuracies
• —The dataset reflects patterns from online medical Q&A platforms, which may not represent clinical best practices
• —Models trained on this data should include appropriate disclaimers about the limitations of AI-generated medical advice

Citation

If you use this dataset, please cite:

@dataset{openmed_meddialog_2026,
  title={MedDialog: A Medical Dialogue Dataset for Clinical Response Generation},
  author={OpenMed},
  year={2026},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/OpenMed/MedDialog}
}

Part of OpenMed

This dataset is part of the OpenMed collection of open medical NLP resources for research and development.