A Survey on Medical Document Summarization: From Machine Learning Techniques to Large Language Models

ABSTRACT The widespread adoption of the Internet has transformed healthcare by enabling the digital storage, sharing, and management of medical documents. This shift has improved information access, enhanced patient care, and opened new avenues for research and innovation. As the volume of medical data available to clinicians and patients continues to grow, the need for effective summarization methods becomes increasingly critical. Recent breakthroughs in deep learning—particularly the emergence of Large Language Models (LLMs)—have further accelerated progress in this area. This paper provides a comprehensive survey of current techniques and emerging trends in medical document summarization. This article is categorized under: Algorithmic Development > Text Mining Application Areas > Health Care

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Publication Details

Journal
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
Published
2025-10-09
DOI
https://doi.org/10.1002/widm.70045
Citations
1
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
2.48
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A Survey on Medical Document Summarization: From Machine Learning Techniques to Large Language Models

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article

A Survey on Medical Document Summarization: From Machine Learning Techniques to Large Language Models

Sriparna Saha, Adam Jatowt, Raghav Jain, Akash Ghosh, Anubhav Jhangra
article en
1 citations

Abstract

ABSTRACT The widespread adoption of the Internet has transformed healthcare by enabling the digital storage, sharing, and management of medical documents. This shift has improved information access, enhanced patient care, and opened new avenues for research and innovation. As the volume of medical data available to clinicians and patients continues to grow, the need for effective summarization methods becomes increasingly critical. Recent breakthroughs in deep learning—particularly the emergence of Large Language Models (LLMs)—have further accelerated progress in this area. This paper provides a comprehensive survey of current techniques and emerging trends in medical document summarization. This article is categorized under: Algorithmic Development > Text Mining Application Areas > Health Care

Wiley Interdisciplinary Reviews Data Mining and Knowledge DiscoveryVol. 15(4)
Indian Institute of Technology Patna (IN), Universität Innsbruck (AT)
Openalex Percentile: Top 8%
Topic Modeling
2.48
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