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BanglaMed-QA: A Question Answering System for Healthcare Support in Bangla — arXiv:2608.28329

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.28329
License (as archived): CC0-1.0
Archived: 2026-10-17T10:48:15.671Z
SHA-256 of the archived text: 78c1dc92fd768aa3b0b899d7bc775177bb4e47f29989d4cf509af051c34928a0
Stable URL of this page: https://metraipolis.com/documento/dc_35a971663a76

How to cite

BanglaMed-QA: A Question Answering System for Healthcare Support in Bangla — arXiv:2608.28329 — arXiv (en), https://arxiv.org/abs/2608.28329 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_35a971663a76 (Metraipolis archive dc_35a971663a76, sha256 78c1dc92fd768aa3b0b899d7bc775177bb4e47f29989d4cf509af051c34928a0)

BibTeX

@misc{dc35a971663a76,
  title = {BanglaMed-QA: A Question Answering System for Healthcare Support in Bangla — arXiv:2608.28329},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.28329},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_35a971663a76; sha256 78c1dc92fd768aa3b0b899d7bc775177bb4e47f29989d4cf509af051c34928a0},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.28329. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Medical question answering (QA) systems have become crucial tools for providing reliable health information. But they remain very unexplored for low-resource languages like Bangla due to limited datasets and systems tailored to these languages. To address this, we introduce BanglaMed-QA, a robust QA system specifically designed for the Bangla medical domain. The process begins with building a structured medical knowledge base that includes 4,493 QA pairs in 9 categories under 506 diseases. To improve semantic comprehension, domain-specific root word dictionaries and synonym sets are proposed, in addition to part-of-speech tagging for anaphora resolution. We adopt supervised machine learning models in which SVM is found to be the best model to categorize questions. Multiple similarity metrics, including cosine, Jaccard, BM25, and Levenshtein, are applied with soft and hard voting methods for query matching. The performance of the QA system has been evaluated in two aspects, with a 95% F1 score in an automated evaluation and an average human satisfaction rating of 0.9 out of 1.0. This validates the real-world application of BanglaMed-QA in closing the healthcare information gap for Bangla speakers.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-08-31 in cs.AI).
Categorie arXiv: Computation and Language (cs.CL) ; Artificial Intelligence (cs.AI); Machine Learning (cs.LG).
Pagina del lavoro: https://arxiv.org/abs/2608.28329 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-17T10:33:42.521Z dalla pagina https://arxiv.org/catchup/cs.AI/2026-08-31?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).