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This study will be conducted to obtain data on oral cancer risk factors to generate machine learning models with good predictive accuracy for stratifying individuals with high-oral cancer risk and delineating high-risk and low-risk oral lesions. Likewise, this study will seek to provide oral cancer-related health education and training on oral-self-examination for beneficiaries
Accuracy of machine learning algorithms for predicting high-risk persons [ Time Frame: 24 months ]
Predictive accuracy of the ML classifiers for forecasting individuals with or likely to develop high-risk lesions within 24 months of first screening encounter based on demographic and lifestyle information.
Accuracy of machine learning algorithms for discriminating high-risk and low-risk lesions [ Time Frame: 24 months ]
Predictive accuracy of ML classifiers for classifying high-risk and low-risk lesions based on demographic and lifestyle risk factors, oral high-risk HPV status, and salivary DNA hypermethylation levels.
Biospecimen Retention: Samples With DNA
Oral rinse samples obtained via drooling in 50cc tubes.
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Layout table for eligibility information
Ages Eligible for Study:
45 Years and older (Adult, Older Adult)
Sexes Eligible for Study:
Accepts Healthy Volunteers:
Hong Kong residents aged 45 years and above residing in Southern and Central and Western district council districts (DCD).
Healthy individuals satisfying age and residential area criteria with no previous history of oral cancer. Individuals with a history of other cancers will be included in the study provided they have been in remission for more than three years.
Participants with reduced mouth opening (irrespective of the cause) to permit proper administration of VOE or photosensitive epilepsy will be excluded. Likewise, those who decline the provision of written consent or participation in any part of the study.