mlsanityData to 7 Oct 2026

Natural Language Processing in Support of Evidence-based Medicine: A Scoping Review

arXiv 2505.22280 ↗First posted 28 May 2025cs.CL cs.AIcited by 2

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Abstract (arXiv)

Evidence-based medicine (EBM) is at the forefront of modern healthcare, emphasizing the use of the best available scientific evidence to guide clinical decisions. Due to the sheer volume and rapid growth of medical literature and the high cost of curation, there is a critical need to investigate Natural Language Processing (NLP) methods to identify, appraise, synthesize, summarize, and disseminate evidence in EBM. This survey presents an in-depth review of 129 research studies on leveraging NLP for EBM, illustrating its pivotal role in enhancing clinical decision-making processes. The paper systematically explores how NLP supports the five fundamental steps of EBM -- Ask, Acquire, Appraise, Apply, and Assess. The review not only identifies current limitations within the field but also proposes directions for future research, emphasizing the potential for NLP to revolutionize EBM by refining evidence extraction, evidence synthesis, appraisal, summarization, enhancing data comprehensibility, and facilitating a more efficient clinical workflow.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 17 of its 155 references that are in the map. First posted on arXiv 28 May 2025.

Builds on

17 of 155 references.

References · 17

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019BioBERT: a pre-trained biomedical language representation model for biomedical text miningcited by 1,935
  3. 2017Get To The Point: Summarization with Pointer-Generator Networkscited by 1,281
  4. 2021MS2: Multi-Document Summarization of Medical Studiescited by 80
  5. 2018A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literaturecited by 79
  6. 2023Large Language Models for Healthcare Data Augmentation: An Example on Patient-Trial Matchingcited by 30
  7. 2024Closing the gap between open-source and commercial large language models for medical evidence summarizationcited by 21
  8. 2022Trial2Vec: Zero-Shot Clinical Trial Document Similarity Search using Self-Supervisioncited by 18
  9. 2023Exploring the Effectiveness of Instruction Tuning in Biomedical Language Processingcited by 16
  10. 2024TriSum: Learning Summarization Ability from Large Language Models with Structured Rationalecited by 10
  11. 2022The Leaf Clinical Trials Corpus: a new resource for query generation from clinical trial eligibility criteriacited by 9
  12. 2023LeafAI: query generator for clinical cohort discovery rivaling a human programmercited by 8
5 more
  1. 2023Automatically Summarizing Evidence from Clinical Trials: A Prototype Highlighting Current Challengescited by 7
  2. 2023Text Classification of Cancer Clinical Trial Eligibility Criteriacited by 7
  3. 2024AlpaPICO: Extraction of PICO Frames from Clinical Trial Documents Using LLMscited by 4
  4. 2021Validating GAN-BioBERT: A Methodology For Assessing Reporting Trends In Clinical Trialscited by 2
  5. 2024A Span-based Model for Extracting Overlapping PICO Entities from RCT Publicationscited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025A Disease-Aware Dual-Stage Framework for Chest X-ray Report Generationcited by 2
  2. 2026Improving Retrieval-Augmented Generation without Taxonomy-based Error Categorizationcited by 1