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Early Detection of Oral Potentially Malignant Disorders: A Review on Prospective Screening Methods with Regard to Global Challenges
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. (MIDA)ORCID iD: 0000-0001-7312-8222
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2022 (English)In: Journal of Maxillofacial and Oral Surgery, ISSN 0972-8279, Vol. 23, no 1, p. 23-32Article in journal (Refereed) Published
Abstract [en]

Oral cancer is a cancer type that is widely prevalent in low-and middle-income countries with a high mortality rate, and poor quality of life for patients after treatment. Early treatment of cancer increases patient survival, improves quality of life and results in less morbidity and a better prognosis. To reach this goal, early detection of malignancies using technologies that can be used in remote and low resource areas is desirable. Such technologies should be affordable, accurate, and easy to use and interpret. This review surveys different technologies that have the potentials of implementation in primary health and general dental practice, considering global perspectives and with a focus on the population in India, where oral cancer is highly prevalent. The technologies reviewed include both sample-based methods, such as saliva and blood analysis and brush biopsy, and more direct screening of the oral cavity including fluorescence, Raman techniques, and optical coherence tomography. Digitalisation, followed by automated artificial intelligence based analysis, are key elements in facilitating wide access to these technologies, to non-specialist personnel and in rural areas, increasing quality and objectivity of the analysis while simultaneously reducing the labour and need for highly trained specialists.

Place, publisher, year, edition, pages
Springer Nature, 2022. Vol. 23, no 1, p. 23-32
Keywords [en]
Artificial intelligence, Assisted screening, Noninvasive methods, Oral cancer, Optical imaging
National Category
Medical and Health Sciences
Research subject
Computerized Image Processing
Identifiers
URN: urn:nbn:se:uu:diva-489656DOI: 10.1007/s12663-022-01710-9ISI: 000782697000001PubMedID: 38312957OAI: oai:DiVA.org:uu-489656DiVA, id: diva2:1715523
Funder
Linköpings universitetVinnova, 2017-02447Vinnova, 2020-03611Available from: 2022-12-02 Created: 2022-12-02 Last updated: 2024-05-14Bibliographically approved

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Lindblad, Joakim

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Haj-Hosseini, NedaLindblad, JoakimHasséus, BengtKumar, Vinay VijayaSubramaniam, NarayanaHirsch, Jan-Michaél
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