{
  "abstract": "Large language models (LLMs) have advanced medical question answering (QA) significantly, yet low-resource languages such as Bangla remain critically underserved. This review examines the current landscape of LLM-based medical QA with a primary focus on Bangla, analyzing 15 representative studies (2022-2026), including English and multilingual works reviewed to contextualize findings for Bangla. We examine methodological approaches, datasets, and evaluation frameworks across diverse paradigms, including transformer architectures, retrieval-augmented generation (RAG), prompt engineering, and parameter-efficient fine-tuning, to identify pathways toward reliable and linguistically inclusive medical AI. The findings reveal a persistent performance gap driven by large-scale domain-specific pretraining and standardized benchmarks in English. Persistent challenges include dataset scarcity, heavy reliance on translated corpora, inconsistent evaluation practices, and a lack of clinician-validated benchmarks. This review identifies these gaps and outlines a structured research roadmap emphasizing native-language corpus development, multimodal data integration, standardized benchmarking, and bias auditing as essential steps toward building reliable and linguistically inclusive medical QA systems for Bangla healthcare.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Computer Science and Engineering, BRAC University, Dhaka, Bangladesh.",
    "Department of Computer Science and Engineering, University of Asia Pacific, Dhaka, Bangladesh.",
    "Department of Computer Science and Engineering, East Delta University, Chittagong, Bangladesh.",
    "ELITE Research Lab, LLC, Queens, New York, NY, United States.",
    "Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia.",
    "Department of CSE, American International University-Bangladesh, Dhaka, Bangladesh."
  ],
  "article_type": "review article",
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Jannatul Somiya Mahmud"
    },
    {
      "affs": [
        1
      ],
      "name": "Khadija Akter Ratri"
    },
    {
      "affs": [
        2
      ],
      "name": "Md Hamid Hosen"
    },
    {
      "affs": [
        3
      ],
      "name": "Md Kishor Morol"
    },
    {
      "affs": [
        4
      ],
      "name": "Liew Tze Hui"
    },
    {
      "affs": [
        3,
        5
      ],
      "name": "Dip Nandi"
    },
    {
      "affs": [
        3,
        5
      ],
      "name": "Abdullah Al Jubair"
    },
    {
      "affs": [
        3,
        5
      ],
      "name": "Mashiour Rahman"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/2trhrtfnqry7k.bib",
  "cited_by": 0,
  "doi": "10.3389/fdgth.2026.1856734",
  "fulltext_url": "https://europepmc.org/articles/PMC13714819",
  "id": "2trhrtfnqry7k",
  "issns": [
    "2673-253X"
  ],
  "landing_url": "https://europepmc.org/article/MED/42953604",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Mini Review"
    ],
    [
      "openalex",
      "2718|Artificial Intelligence in Healthcare and Education"
    ]
  ],
  "openalex": "W7221774942",
  "pdf_url": "https://europepmc.org/articles/PMC13714819?pdf=render",
  "pmcid": "PMC13714819",
  "pmid": "42953604",
  "published": "2026-10-14",
  "publisher": "Frontiers Media SA",
  "ris": "https://research.draconitic.com/paper/2trhrtfnqry7k.ris",
  "sources": [
    {
      "first_seen": "2026-10-31T00:20:41Z",
      "native_id": "MED:42953604",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42953604"
    },
    {
      "first_seen": "2026-11-01T12:22:14Z",
      "native_id": "PMC13714819",
      "source": "pmc",
      "url": "https://doi.org/10.3389/fdgth.2026.1856734"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2718|Artificial Intelligence in Healthcare and Education",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "A mini-review of medical question answering for Bangla: the methodological landscape and cross-lingual perspectives.",
  "title_text": "A mini-review of medical question answering for Bangla: the methodological landscape and cross-lingual perspectives.",
  "type": "peer-reviewed",
  "updated_at": "2026-11-01T12:22:14Z",
  "url": "https://research.draconitic.com/paper/2trhrtfnqry7k",
  "venue": "Frontiers in digital health",
  "versions": []
}