Explainable AI for Disease Detection and Body Constitution Analysis Using Tongue Imaging: A Deep Learning Approach for Non-Invasive Diagnostics

Deep learning, specifically CNNs and multi-task learning models, is revolutionizing the task of disease classification in tongue imaging. This has been applied for reporting latest results on detection of pathological characteristics such as coatings, cracks, and discoloration. Hybrid frameworks, which have combined segmentation and classification together, improved the diagnostic accuracy especially when distinguishing between related disorders. Combining data-driven methodologies with a knowledge base on traditional medicine, AI models will be able to present comprehensive health diagnoses. Integration of these scalable solutions into a simple, mobile application can make such solutions available to a much wider audience. This breakthrough demonstrates how deep learning can transform healthcare using non-invasive, precise, and objective diagnostic tools. All these models will get further refinements such as lesion types and large datasets, eventually culminating into better accurate trustworthy medical diagnostics.