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Machine Learning Applications for Venous Ulcer Assessment and Wound Care: A Review.

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Machine learning (ML) models are advancing venous ulcer wound care. This review analyzed 79 studies from 2001-2025, summarizing ML applications, benefits, and future research directions in chronic wound management.

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chronic woundsmachine learningvenous ulcerswound care

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Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Medicine
  • Wound Care Research

Background:

  • Venous ulcer wound care has seen significant progress with machine learning (ML) integration.
  • A comprehensive analysis of existing research is crucial to understand ML's impact.

Purpose of the Study:

  • To systematically analyze research on ML applications in venous ulcer wound care from 2001 to August 2025.
  • To identify trends, benefits, limitations, and future research opportunities in this domain.

Main Methods:

  • Systematic literature search across Web of Science, Scopus, and PubMed.
  • Inclusion/exclusion criteria applied to derive 79 relevant studies for analysis.
  • Meta-analysis and detailed examination of ML model applications in venous ulcer care.

Main Results:

  • Analysis of 79 studies reveals diverse applications of ML models in venous ulcer wound management.
  • Identified benefits for healthcare systems and patients, alongside ML model limitations.
  • Discussion includes current trends, opportunities, and limitations of existing research.

Conclusions:

  • ML models offer significant potential to enhance venous ulcer wound care.
  • Further research is needed to address limitations and explore broader applications in chronic wound management.
  • This review provides valuable insights for researchers in ML and wound care.