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The Potential Role of AI- and Machine Learning Models in the Early Detection of Oral Cancer and Oral Potentially
Cynthia Groenevelt1,2,3, Mirjam Fransen2,3, Jos Poell4
1Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, eHealth Living and Learning Lab Amsterdam, Amsterdam, The Netherlands.
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.
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