Machine learning and treatment outcome prediction for oral cancer

Background The natural history of oral squamous cell carcinoma (OSCC) is complicated by progressive disease including loco‐regional tumour recurrence and development of distant metastases. Accurate prediction of tumour behaviour is crucial in delivering individualized treatment plans and developing optimal patient follow‐up and surveillance strategies. Machine learning algorithms may be employed in oncology research to improve clinical outcome...