Dataset Card for BanglaMedQA and BanglaMMedBench

This dataset introduces BanglaMedQA and BanglaMMedBench, the first large-scale Bangla biomedical Multiple Choice Question (MCQ) datasets designed to evaluate reasoning and retrieval-based methods such as Retrieval-Augmented Generation (RAG) for Bangla Question Answering.

Dataset Details

Dataset Description

BanglaMedQA consists of 1,000 MCQs collected from authentic Bangladeshi medical admission exams (MBBS, BDS, AFMC) between 1990 and 2024, each with reasoning for the correct answer.
BanglaMMedBench contains 1,000 scenario-based medical questions translated from the English MMedBench dataset using Gemini-1.5-Flash, reviewed by medical experts for domain and linguistic accuracy.

• Curated by: Department of Computer Science and Engineering, Islamic University of Technology (IUT), Bangladesh
• Funded by [optional]: IUT Research Fund
• Shared by [optional]: Sadia Sultana, Saiyma Sittul Muna, Mosammat Zannatul Samarukh, Ajwad Abrar, Tareque Mohmud Chowdhury
• Language(s) (NLP): Bangla
• License: Not given

Dataset Sources [optional]

• Repository: https://huggingface.co/datasets/ajwad-abrar/BanglaMedQA
• Paper [optional]: BanglaMedQA and BanglaMMedBench: Evaluating Retrieval-Augmented Generation Strategies for Bangla Biomedical Question Answering (arXiv:2511.04560v1)
• Demo [optional]: Not given

Uses

Direct Use

• Benchmarking Bangla biomedical QA systems
• Evaluating Retrieval-Augmented Generation (RAG) and reasoning strategies
• Studying translation and reasoning robustness across English–Bangla in medical domains

Out-of-Scope Use

• Not suitable for clinical or diagnostic use
• Not to be used for real patient advice or decision-making
• Should not replace professional medical education or assessment materials

Dataset Structure

Each dataset contains 1,000 entries with the following fields:

• question: Medical question in Bangla
• options: Four options labeled A, B, C, D
• answer: Correct option label
• rationale: Explanation for the correct answer

No predefined train/test/validation split is provided; users may define splits as needed.

Dataset Creation

Curation Rationale

The datasets were created to fill the gap in Bangla biomedical QA resources and to evaluate retrieval-augmented reasoning performance in low-resource languages for educational and AI research purposes.

Source Data

Data Collection and Processing

• BanglaMedQA:
  • Sourced from 34 years of official Bangladeshi medical admission exams.
  • Removed ambiguous or duplicate questions.
  • Standardized multiple-choice formats and corrected inconsistencies.
• BanglaMMedBench:
  • Translated from English MMedBench using Gemini-1.5-Flash.
  • Manually verified for medical and linguistic accuracy by domain experts.
  • Formatting and alignment corrected post-translation.

Who are the source data producers?

• Medical admission exam boards of Bangladesh (MBBS, BDS, AFMC)
• Original MMedBench dataset creators

Annotations [optional]

Annotation process

Each question includes a verified rationale explaining the correct answer.
Quality control was performed by IUT researchers and reviewed by medical experts for correctness and clarity.

Who are the annotators?

Undergraduate and graduate students at IUT under faculty supervision, with medical domain experts validating the rationales.

Personal and Sensitive Information

No personal or sensitive data are included.
The datasets contain only educational biomedical content.

Bias, Risks, and Limitations

• Translation from English may cause minor semantic drift.
• OCR-based textbook corpus may introduce small transcription errors.
• Dataset size (2,000 questions total) may limit generalization to broader medical subfields.
• Rationale style and vocabulary may reflect academic exam phrasing.

Recommendations

Use these datasets for benchmarking and research only.
Cross-verify terminology when building multilingual or fine-tuned models.
Do not apply outputs in real-world medical or diagnostic settings.

Citation [optional]

BibTeX:

@article{Sultana2025BanglaMedQA,
  title={BanglaMedQA and BanglaMMedBench: Evaluating Retrieval-Augmented Generation Strategies for Bangla Biomedical Question Answering},
  author={Sultana, Sadia and Muna, Saiyma Sittul and Samarukh, Mosammat Zannatul and Abrar, Ajwad and Chowdhury, Tareque Mohmud},
  year={2025},
  journal={arXiv preprint arXiv:2511.04560},
  url={https://arxiv.org/abs/2511.04560v1}
}