Abstract:Biliary tract cancers (BTC), including intrahepatic cholangiocarcinoma, perihilar cholangiocarcinoma, distal cholangiocarcinoma, and gallbladder cancer, are relatively rare but carry a poor prognosis due to difficulties in diagnosis and limited therapeutic options. With the rapid advancement of artificial intelligence (AI), particularly machine learning and deep learning, its applications in clinical medicine have expanded substantially. This review summarizes the current progress of AI in BTC, focusing on its roles in diagnosis, prognostic evaluation, therapeutic decision-making, and recurrence prediction. The strengths and limitations of various AI models are discussed, alongside the challenges of clinical translation and potential future directions. The integration of AI into BTC management is expected to facilitate earlier detection, enhance personalized treatment strategies, and ultimately improve patient outcomes.