Decoding Chronic Orofacial Pain: Neuroimmune Crosstalk, Digital Phenotyping, and Artificial Intelligence for Precision Pain Medicine

Review Article

Abstract

Chronic orofacial pain is difficult to classify because similar symptoms may arise from different biological mechanisms, and symptom-based diagnoses often fail to explain why pain persists or to predict treatment response. This narrative review examines whether chronic orofacial pain can be reclassified according to biological mechanism rather than clinical symptom, and how emerging technologies might support that shift. It describes the mechanism-based framework of nociceptive, neuropathic, and nociplastic pain, together with the neuroimmune interactions, including microglial activation, peripheral neuroinflammation, cytokine signaling, and central sensitization, that sustain pain. It then considers digital phenotyping through wearable sensors, smartphone data, sleep tracking, jaw-movement analysis, and facial behavior, and the role of machine learning, radiomics, and multimodal artificial intelligence in multidimensional diagnosis. Finally, it outlines precision therapeutics through patient stratification, biomarkers, neuromodulation, and individualized pharmacological and behavioral care. Evidence supports a mechanism-informed direction, although prospective validation and standardization are still necessary before routine use.