Datasets:

NaghmehAI
/

PerMedCQA

PerMedCQA is the first large-scale, real-world benchmark for Persian-language medical consumer question answering. It contains anonymized medical inquiries from Persian-speaking users paired with professional responses, enabling rigorous evaluation of large language models in low-resource, health-related domains.

📊 Dataset Overview

Total entries: 68,138 QA pairs
Source platforms: DrYab, HiSalamat, GetZoop, Mavara-e-Teb
Timeframe: Nov 10, 2022 – Apr 2, 2024
Languages: Persian only
Licensing: CC BY-NC-SA 4.0
🔗 Paper
📄 Paper on arXiv
📊 Paper with Code page

🧬 Metadata & Features

Each example in the dataset includes:

instance_id: Unique ID for each QA pair
Title: Short user-submitted title
Question: Full Persian-language consumer medical question
Expert_Answer: Doctor’s response
Category: Medical topic (e.g., “پوست و مو”)
Specialty: Expert’s medical field (e.g., “متخصص پوست و مو”)
Age: Reported patient age
Weight: Reported weight (optional)
Sex: Patient gender ("man" or "woman")
dataset_source: Name of the platform (e.g., DrYab, Getzoop)
Tag: ICD‑11 label and rationale
QuestionType: Question classification tag (e.g., "Contraindication", "Indication") and reasoning

📁 Dataset Structure

{
  "Title": "قرمزی پوست نوزاد بعد از استفاده از پماد",
  "Category": "پوست و مو",
  "Specialty": "متخصص پوست و مو",
  "Age": "1",
  "Weight": "10",
  "Sex": "man",
  "dataset_source": "HiSalamat",
  "instance_id": 32405,
  "Tag": {
    "Tag": 23,
    "Tag_Reasoning": "The question addresses a skin reaction in an infant following the application of a cream, indicating a dermatological condition."
  },
  "Question": "سلام خسته نباشید. من واسه پسر ۱ ساله‌ام که جای واکسنش سفت شده بود، پماد موضعی استفاده کردم. ولی الان پوستش خیلی قرمز شده و خارش داره. ممکنه حساسیت داده باشه؟ باید چکار کنم؟",
  "Expert_Answer": "احتمالا پوست نوزاد به ترکیبات پماد حساسیت نشان داده است. مصرف آن را قطع کنید و در صورت ادامه علائم به متخصص پوست مراجعه کنید.",
  "QuestionType": {
    "Explanation": "The user asks about an adverse skin reaction following the use of a topical medication on an infant, which is a case of possible side effects.",
    "QuestionType_Tag": "SideEffect"
  }
}

📥 How to Load

from datasets import load_dataset

ds = load_dataset("NaghmehAI/PerMedCQA", split="train")
print(ds[0])

🚀 Intended Uses

🧠 Evaluation of multilingual or Persian-specific LLMs in real-world, informal medical domains
🛠️ Few-shot or zero-shot fine-tuning, instruction-tuning
🌍 Cultural insights: Persian language behavior in health-related discourse
⚠️ NOT for clinical use: Informational and research purposes only

⚙️ Data Processing Pipeline

Stage 1: Column Transformation (`change_columns.py`)

Reads CSV/JSON input and transforms them into structured JSON format
Handles single-turn, multi-turn, and multi-expert Q&A data
Cleans and formats the text, removing unnecessary whitespace and newlines
Creates a chat-style JSON file with user and assistant roles

Stage 2: QA Preprocessing (`preprocess_for_qa.py`)

Truncates multi-turn dialogues to first Q&A pair
Removes:
- Empty or invalid messages
- Q&A pairs shorter than 3 words
- Duplicate Q&A instances
Adds:
- dataset_source and instance_id to each item
Merges cleaned records into All_QA_preprocessed.json

Dataset Cleaning Results:

Dataset	Step 1 Removed	Step 2 Removed	Step 3 Removed	Final Records
Dr_Yab	63	1083	25	37,905
GetZoop	1005	1352	8	25,502
Hi-Salamat	9580	121	1	5,220
Mavara-e-Teb	0	1034	92	4,789

📚 Citation

If you use PerMedCQA, please cite:

@misc{jamali2025permedcqa,
  title={PerMedCQA: Benchmarking Large Language Models on Medical Consumer Question Answering in Persian Language},
  author={Jamali, Naghmeh and Mohammadi, Milad and Baledi, Danial and Rezvani, Zahra and Faili, Heshaam},
  year={2025},
  eprint={2505.18331},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2505.18331}
}

📬 Contact

For collaboration or questions:

📧 Naghmeh Jamali – naghme.jamali.ai@gmail.com, Milad Mohammadi – miladmohammadi@ut.ac.ir, Danial Baledi – baledi.danial@gmail.com.

PerMedCQA: Persian Medical Consumer QA Benchmark