@article{10.37349/emed.2026.1001413,
abstract = {Artificial intelligence (AI) is transforming clinical decision-making across cranio-maxillofacial trauma, oral health, and systemic disease. These domains are increasingly recognised as biologically and clinically interconnected, yet they are often studied and managed independently. This perspective introduces the concept of an integrative triangle linking facial trauma, oral health, and systemic disease, with AI serving as the computational bridge that enables cross-domain modelling and coordinated care. AI applications within this framework include imaging-based fracture detection, patient-specific implant design, automated oral disease diagnosis, multimodal risk prediction, and longitudinal outcome modelling. By integrating imaging, clinical, laboratory, and behavioural data, AI can identify shared inflammatory and metabolic pathways influencing trauma recovery and chronic disease progression. This closed-loop paradigm supports continuous learning, allowing outcomes in one domain to inform prediction and intervention in the others. The integrative triangle provides a translational roadmap for precision medicine, moving from isolated prediction toward coordinated prevention and intervention. Future development will require multimodal data integration, prospective validation, and responsible governance to ensure explainable and equitable AI deployment. This framework positions facial trauma and oral health as central components of systemic precision medicine and highlights AI as a catalyst for integrated, patient-centred care.},
author = {Pham, Tuan D.},
doi = {10.37349/emed.2026.1001413},
journal = {Exploration of Medicine},
elocation-id = {1001413},
title = {Artificial intelligence for the integrative triangle: facial trauma, oral health, and systemic diseases},
url = {https://www.explorationpub.com/Journals/em/Article/1001413},
volume = {7},
year = {2026}
}