The promise of artificial intelligence and internet of things in oral cancer detection

Abstract

The significance of artificial intelligence (AI) and the internet of things (IoT) in improving oral cancer detection is critically assessed in this letter. Oral cancer is a major worldwide health concern that is frequently detected at a late stage, resulting in a poor prognosis. AI techniques, in particular machine learning and deep learning models, show great promise for accurately assessing digital images and histopathology slides, assisting physicians in risk assessment and early identification. Furthermore, real-time monitoring and surveillance are made possible by IoT-enabled devices, which gather important patient data for the early identification of indications of oral cancer. Furthermore, the performance and efficacy of diagnosis have been improved by developments in image processing algorithms, which helps to avoid delayed diagnosis. Big data analytics and the application of salivary biomarkers enhance early detection initiatives. To battle oral cancer, a variety of AI and IoT strategies are being investigated, in addition to other AI uses. Although encouraging developments, application in clinical practice will not be successful unless issues with validation, standardization, data privacy and regulatory compliance are resolved. Working together, healthcare stakeholders can promote innovation, validate techniques and get over current obstacles. To reduce the prevalence of oral cancer, future directions include the creation of multimodal imaging methods and their incorporation into population-based screening initiatives. We can move closer to early detection, individualized therapy and prevention of oral cancer by utilizing AI and IoT, which will ultimately improve patient outcomes.