Prediction of the Need for Anticonvulsants in the Management of Orofacial Neuropathic Pain Using Machine Learning.

Abstract

Background and aim Orofacial neuropathic pain is a medical condition caused by a lesion or dysfunction of the nervous system and is one of the most challenging for dental clinicians to diagnose. Anticonvulsants, antidepressants, analgesics, nonsteroidal anti-inflammatory drugs, and other classes of medications are frequently used to treat this condition. Our study aimed to build a machine learning-based classifier to predict the need for anticonvulsant drugs in patients with orofacial neuropathic pain. Materials and methods A machine learning tool that was trained and tested on patients for predicting and detecting algorithms, which would in turn predict the need for anticonvulsants in the treatment of orofacial neuropathic pain, was employed in this study. Results Three machine learning algorithms successfully detected and predicted the need for anticonvulsants to treat patients with orofacial neuropathic pain. All three models showed a high accuracy, that is, 97%, 94%, and 89%, in predicting the need for anticonvulsants. Conclusion Machine learning algorithms can accurately predict the need for anticonvulsant drugs for treating orofacial neuropathic pain. Further research is needed to validate these findings using larger sample sizes and imaging modalities.