Prof. Tianxin Lin delivered an insightful presentation on the application of artificial intelligence in the precision diagnosis and treatment of bladder cancer. He highlighted the current diagnostic challenges related to imaging sensitivity, endoscopic evaluation, and pathological workload, all of which can impact timely and accurate treatment decisions. Prof. Lin introduced the development of an AI-assisted multi-parameter preoperative lymph node metastasis prediction system, aiming to improve staging accuracy and guide optimal surgical planning. He also shared data from AI-based lesion segmentation studies published in Nature Biomedical Engineering, demonstrating the potential of deep learning models in improving diagnostic performance and reducing diagnostic variability in clinical practice.
