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The Potential Role of AI- and Machine Learning Models in the Early Detection of Oral Cancer and Oral Potentially Malignant Disorders

  • Amsterdam UMC
  • University of Amsterdam
  • Vrije Universiteit Amsterdam

Research output: Contribution to journalArticleAcademicpeer-review

25 Downloads (Pure)

Abstract

INTRODUCTION: Artificial Intelligence (AI) is playing an increasing role in advancing diagnostic processes and decision-making in healthcare. In the early detection of oral cancer and oral potentially malignant disorders (OPMDs), its role is still being explored. This paper evaluates advancements in AI applications for the early detection of oral cancer and OPMDs. METHODS: A narrative umbrella review was performed on reviews that explicitly evaluated non-invasive diagnostic techniques combined with AI-modalities or machine learning techniques in the early detection of oral cancer and OPMDs. RESULTS: Key findings of eight studies published between 2015 and 2024 demonstrate various AI-modalities and their diagnostic accuracy, accessibility and affordability, limitations and challenges and ethical and regulatory needs. CONCLUSION: AI- and deep learning models hold promise in improving the early detection of oral cancer and OPMDs, offering high diagnostic accuracy that can significantly enhance patient outcomes. Challenges such as limited explainability and ethical concerns must be addressed to fully integrate these technologies into daily clinical practice.
Original languageEnglish
Pages (from-to)147-151
Number of pages5
JournalStudies in health technology and informatics
Volume326
DOIs
Publication statusPublished - 12 May 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • AI
  • Machine learning models
  • Oral Potentially Malignant Disorders
  • early detection
  • non-invasive diagnostic techniques
  • oral cancer
  • oral precancer

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