Machine learning effective in predicting oral cancer risk
According to a recent study, visual oral examination (VOE) was performed among 1467 participants of a community-based screening program. Each individual's status was defined as positive/negative for oral cancer and histologic confirmation of epithelial dysplasia (ED) and squamous cell carcinoma (SCC) was performed for positive status.
Information on demography, habitual, lifestyle and familial risk factors was obtained, and expired carbon monoxide levels (in ppm) were assessed using a monitor. Input features and histologic diagnoses were used to populate 12 machine learning algorithms. And the study then demonstrated that machine learning is a successful tool for predicting oral cancer risk and may be applied to identify 'at-risk populations' in opportunistic and organized screening.
Reference: Meeting Announcement INTERNATIONAL & AMERICAN ASSOCIATIONS FOR DENTAL RESEARCH; https://www.iadr.org/about/news-reports/press-releases/machine-learning-predicts-oral-cancer.
Dr. Nandita Mohan
BDS, MDS( Pedodontics and Preventive Dentistry)