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AraHealthQA 2025: The First Shared Task on Arabic Health Question Answering

Published: August 27, 2025 | arXiv ID: 2508.20047v3

By: Hassan Alhuzali , Walid Al-Eisawi , Muhammad Abdul-Mageed and more

Potential Business Impact:

Helps computers answer health questions in Arabic.

Business Areas:
Natural Language Processing Artificial Intelligence, Data and Analytics, Software

We introduce AraHealthQA 2025, the Comprehensive Arabic Health Question Answering Shared Task, held in conjunction with ArabicNLP 2025 (co-located with EMNLP 2025). This shared task addresses the paucity of high-quality Arabic medical QA resources by offering two complementary tracks: MentalQA, focusing on Arabic mental health Q&A (e.g., anxiety, depression, stigma reduction), and MedArabiQ, covering broader medical domains such as internal medicine, pediatrics, and clinical decision making. Each track comprises multiple subtasks, evaluation datasets, and standardized metrics, facilitating fair benchmarking. The task was structured to promote modeling under realistic, multilingual, and culturally nuanced healthcare contexts. We outline the dataset creation, task design and evaluation framework, participation statistics, baseline systems, and summarize the overall outcomes. We conclude with reflections on the performance trends observed and prospects for future iterations in Arabic health QA.

Country of Origin
πŸ‡ΈπŸ‡¦ πŸ‡ΊπŸ‡Έ United States, Saudi Arabia

Page Count
11 pages

Category
Computer Science:
Computation and Language