Alabi RO, Elmusrati M, Sawazaki-Calone I, et al. - Experts investigated the use of artificial neural networks (ANNs) to prognosticate recurrences in early-stage oral tongue squamous cell carcinoma (OTSCC). A Web-based tool accessible for public use was also made. For prognostication of locoregional recurrences in early OTSCC, a feedforward neural network was trained. The most significant prognosticators to predict locoregional recurrence were tumor budding and depth of invasion, as recognized by this neural network model. The exactitude of the neural network was 92.7%, which was greater compared with that of the logistic regression model (86.5%). This online tool gave 88.2%, 71.2%, and 98.9% accuracy, sensitivity, and specificity, respectively. In summary, ANN appears to give a distinctive decision-making support prognosticating recurrences and hence adding value for the management of early OTSCC. To the best of knowledge, for prognostication of recurrence in early OTSCC, this was the first study that used ANN and it gave a web-based tool.