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Artificial intelligence in dentistry:Harnessing big data to predict oral cancer survival

World Journal of Clinical Oncology 2020年第11期11卷 918-934页

作者： Man Hung jungweon park Eric S Hon Jerry Bounsanga Sara Moazzami Bianca Ruiz-Negrón Dawei Wang College of Dental Medicine Roseman University of Health SciencesSouth JordanUT 84095United States Department of Orthopaedic Surgery Operations University of UtahSalt Lake CityUT 84108United States College of Social Work University of UtahSalt Lake CityUT 84112United States Division of Public Health University of UtahSalt Lake CityUT 84108United States Department of Educational Psychology University of UtahSalt Lake CityUT 84109United States Department of Economics University of ChicagoChicagoIL 60637United States Research Section Utah Medical Education CouncilSalt Lake CityUT 84102United States College of Social and Behavioral Sciences University of UtahSalt Lake CityUT 84112United States Data Analytics Unit Walmart Inc.BentonvilleAR 72716United States

BACKGROUND Oral cancer is the sixth most prevalent cancer *** knowledge in oral cancer risk factors and survival is *** To come up with machine learning(ML)algorithms to predict the length of survival for individuals diagnosed with oral cancer,and to explore the most important factors that were responsible for shortening or lengthening oral cancer *** We used the Surveillance,Epidemiology,and End Results database from the years 1975 to 2016 that consisted of a total of 257880 cases and 94 *** ML techniques in the area of artificial intelligence were applied for model training and *** accuracy was evaluated using mean absolute error(MAE),mean squared error(MSE),root mean squared error(RMSE),R2 and adjusted *** The most important factors predictive of oral cancer survival time were age at diagnosis,primary cancer site,tumor size and year of *** of diagnosis referred to the year when the tumor was first diagnosed,implying that individuals with tumors that were diagnosed in the modern era tend to have longer survival than those diagnosed in the *** extreme gradient boosting ML algorithms showed the best performance,with the MAE equaled to 13.55,MSE 486.55 and RMSE *** Using artificial intelligence,we developed a tool that can be used for oral cancer survival prediction and for medical-decision *** finding relating to the year of diagnosis represented an important new discovery in the *** results of this study have implications for cancer prevention and education for the public.

关键词： Oral cancer survival Machine learning Artificial intelligence Dental medicine Public health Surveillance,Epidemiology,and End Results Quality of life

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