AI-Integrated precision medicine for otorhinolaryngology: Advancing biomarkers, predictive analytics, and personalized therapeutic strategies

Abstract

Artificial intelligence is rapidly redefining precision medicine within otorhinolaryngology, allowing individualized approaches to disease diagnosis, prognosis, and therapeutic decision-making involving ear, nose, throat, and head-neck disorders.The integration of multi-omics biomarkers, radiomics, digital pathology, advanced imaging, and clinical data with machine learning and deep learning models has significantly improved the diagnostics of such conditions as chronic rhinosinusitis, otitis media, hearing loss, sleep disorder, and head-neck cancers.AI-driven predictive analytics enable the early identification of high-risk profiles, stratification of disease endotypes, and forecasting of treatment outcomes, whereas personalized therapeutic strategies, including tailored pharmacotherapy, image-guided interventions, and precision oncology, are increasingly achievable.Further innovations, like digital twins, automated endoscopic interpretation, and AI-enhanced surgical navigation, will additionally support real-time clinical decision-making and individualized patient care.In this review, the state-ofthe-art advances in AI-enabled precision medicine within otorhinolaryngology will be discussed, highlighting clinical applications across the range of ENT subspecialties, challenges, ethical considerations, and future directions for integrating AI into personalized ENT practice.

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