Introduction 
OPMDRisk is a tool based on machine learning techniques to predict the histopathological risk level of patients with oral potentially malignant disorders (OPMDs). It takes a patient's non-invasive oral examination results and his/her personal information as input, and returns the predicted histopatholgocial risk level. The non-invasive oral examinations include toluidine blue (TB) staining and visually enhanced lesion scope (VEL scope); while the personal information includes age and lesion conditions (such as site, infiltration and clinical expression) obtained from conventional oral examinations. By integrating the two non-invasive oral assays and the personal information, OPMDRisk achieves a relatively high prediction accuracy of around 90%, which helps to reduce misclassifications of high-risk patients as low-risk, and to prevent possible delays in treatment of high-risk patients.
Data 
The personalized model is built by applying classification method of random forests to the data collected by us in the last several years. In order to further improve the model, we welcome colleagues to contact us for submitting the non-invasive and conventional oral examination data as well as the corresponding histopathology results.
Contact 
We welcome any suggestion and feedback, please contact us at zhouhm@scu.edu.cn or liangzhi@ustc.edu.cn .
Statistics 
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Personal information

Personal lesion conditions

Non-invasive oral assays

Optional information