Research on Automatic Classification Methods for Tibetan Medicine Urine Diagnosis Images

Tibetan medicine, one of the four major traditional medical systems in the world, employs urine diagnosis as a unique and widely used method for disease identification in Tibetan medicine. This study developed a joint classification model that leverages deep neural networks to classify the features and attributes of images of urine used in Tibetan medicine. Tested on a dataset collected in real-world conditions, the model demonstrated a classification accuracy of up to 93.6%, laying a solid foundation for the future development of decision-support platforms specifically designed for urine diagnosis in Tibetan medicine.