Sign inGet started
Dataset · Hugging Face

HPAI-BSC/medical-specialities

Medical Question Classification Dataset Dataset Summary This dataset is designed for medical language models evaluation. It merges several of the most important medical QA datasets into a common format and classifies them into 35 distinct medical categories. This structure enables users to identify any specific categories where the model's performance may be lacking and address these areas accordingly. Dataset Structure Data Fields… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/medical-specialities.

Author / organizationHPAI-BSC
Downloads903 (as reported by Hugging Face)
Likes7
Created11 July 2024
Last updated at source18 November 2025
medicalclassificationquestion-answeringLLMshuggingface
Embed this entry
<iframe src="https://silytics.si/embed/item/a552cc5f-0cdf-4ee6-9ad1-0ebb2fb50253" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Popularity, last 5 days

903 now (-70 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.

Recent changes

  • 16 Oct 2026 Description: Medical Question Classification Dataset Dataset Summary This dataset is designed for medical language models evaluation. It merges several of the most important medical QA datasets into a common format and classifies them into 35 distinct m → Medical Question Classification Dataset Dataset Summary This dataset is designed for medical language models evaluation. It merges several of the most important medical QA datasets into a common format and classifies them into 35 distinct m

Changes detected by Silytics between refreshes of the source.

More from HPAI-BSC

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 20 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.