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Biomedical Question Answering: A Survey of Approaches and Challenges

arXiv 2102.05281 ↗First posted 10 Feb 2021cs.CLcited by 46

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Abstract (arXiv)

Automatic Question Answering (QA) has been successfully applied in various domains such as search engines and chatbots. Biomedical QA (BQA), as an emerging QA task, enables innovative applications to effectively perceive, access and understand complex biomedical knowledge. There have been tremendous developments of BQA in the past two decades, which we classify into 5 distinctive approaches: classic, information retrieval, machine reading comprehension, knowledge base and question entailment approaches. In this survey, we introduce available datasets and representative methods of each BQA approach in detail. Despite the developments, BQA systems are still immature and rarely used in real-life settings. We identify and characterize several key challenges in BQA that might lead to this issue, and discuss some potential future directions to explore.

Key facts. Cited by 46 papers in the map (data through 7 Oct 2026). Builds on 96 of its 246 references that are in the map. First posted on arXiv 10 Feb 2021.

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96 of 246 references.

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Citing papers per year: 2021: 2; 2022: 8; 2023: 18; 2024: 7; 2025: 6; 2026: 5.

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  1. 2023MedCPT: Contrastive Pre-trained Transformers with Large-scale PubMed Search Logs for Zero-shot Biomedical Information Retrievalcited by 182
  2. 2023A Survey of Large Language Models in Medicine: Progress, Application, and Challengecited by 123
  3. 2023Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Healthcited by 118
  4. 2023GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical Informationcited by 115
  5. 2022BioBART: Pretraining and Evaluation of A Biomedical Generative Language Modelcited by 83
  6. 2023Better to Ask in English: Cross-Lingual Evaluation of Large Language Models for Healthcare Queriescited by 82
  7. 2023Benchmarking large language models for biomedical natural language processing applications and recommendationscited by 78
  8. 2023Matching Patients to Clinical Trials with Large Language Modelscited by 68
  9. 2024Improving Retrieval-Augmented Generation in Medicine with Iterative Follow-up Questionscited by 54
  10. 2025MedicalAgentsBench for Complex Medical Reasoning: Comparing Internalized Reasoning Models versus Externalized Agent-based Frameworkscited by 38
  11. 2023HealthFC: Verifying Health Claims with Evidence-Based Medical Fact-Checkingcited by 35
  12. 2023RAMM: Retrieval-augmented Biomedical Visual Question Answering with Multi-modal Pre-trainingcited by 31
34 more
  1. 2023BioInstruct: Instruction Tuning of Large Language Models for Biomedical Natural Language Processingcited by 25
  2. 2021UNIQORN: Unified Question Answering over RDF Knowledge Graphs and Natural Language Textcited by 17
  3. 2023PubMed and Beyond: Biomedical Literature Search in the Age of Artificial Intelligencecited by 16
  4. 2022A Survey on Medical Document Summarizationcited by 14
  5. 2024Progress and Opportunities of Foundation Models in Bioinformaticscited by 13
  6. 2023DORIS-MAE: Scientific Document Retrieval using Multi-level Aspect-based Queriescited by 11
  7. 2023Product Question Answering in E-Commerce: A Surveycited by 10
  8. 2022BIOS: An Algorithmically Generated Biomedical Knowledge Graphcited by 9
  9. 2024BioMamba: Domain-Adaptive Biomedical Language Modelscited by 8
  10. 2022An Accurate Unsupervised Method for Joint Entity Alignment and Dangling Entity Detectioncited by 7
  11. 2025Structured Outputs Enable General-Purpose LLMs to be Medical Expertscited by 6
  12. 2023Large-Scale Knowledge Synthesis and Complex Information Retrieval from Biomedical Documentscited by 5
  13. 2025Memorization in Large Language Models in Medicine: Prevalence, Characteristics, and Implicationscited by 5
  14. 2023Large Language Models are In-context Teachers for Knowledge Reasoningcited by 4
  15. 2025BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactionscited by 4
  16. 2022Development of an Extractive Clinical Question Answering Dataset with Multi-Answer and Multi-Focus Questionscited by 3
  17. 2022BioADAPT-MRC: Adversarial Learning-based Domain Adaptation Improves Biomedical Machine Reading Comprehension Taskcited by 3
  18. 2022SpaceQA: Answering Questions about the Design of Space Missions and Space Craft Conceptscited by 3
  19. 2024Question answering systems for health professionals at the point of care -- a systematic reviewcited by 3
  20. 2024Entry-level guide to the use of large language models for medical researchcited by 3
  21. 2023Exploring Partial Knowledge Base Inference in Biomedical Entity Linkingcited by 2
  22. 2023Generating Explanations in Medical Question-Answering by Expectation Maximization Inference over Evidencecited by 2
  23. 2024A Two-Stage Proactive Dialogue Generator for Efficient Clinical Information Collection Using Large Language Modelcited by 2
  24. 2026Large Language Models Lack Temporal Awareness of Medical Knowledgecited by 2
  25. 2026Towards Next-Generation Healthcare: A Survey of Medical Embodied AI for Perception, Decision-Making, and Actioncited by 2
  26. 2022A Survey on Conversational Search and Applications in Biomedicinecited by 1
  27. 2026BELIEF: Structured Evidence Modeling and Uncertainty-Aware Fusion for Biomedical Question Answeringcited by 1
  28. 2021Recent Advances in Automated Question Answering In Biomedical Domaincited by 0
  29. 2023Using Weak Supervision and Data Augmentation in Question Answeringcited by 0
  30. 2024A Question Answering Based Pipeline for Comprehensive Chinese EHR Information Extractioncited by 0
  31. 2025RAG-BioQA: A Retrieval-Augmented Generation Framework for Long-Form Biomedical Question Answeringcited by 0
  32. 2025Biomedical Hypothesis Explainability with Graph-Based Context Retrievalcited by 0
  33. 2026UETQuintet at BioCreative IX -- MedHopQA: Enhancing Biomedical QA with Selective Multi-hop Reasoning and Contextual Retrievalcited by 0
  34. 2026Adaptive Memory and Reflection Multi-Agent System for Medical Question Answeringcited by 0