Artificial intelligence in the diagnosis and prognosis of intrahepatic cholangiocarcinoma: Applications and challenges

Intrahepatic cholangiocarcinoma (ICC) is a primary liver malignancy with increasing global incidence and mortality rates. The 5-year overall survival rate for patients with ICC is approximately 9%. Surgical resection currently represents the only curative treatment option. However, due to the high aggressiveness, insidious onset, and atypical clinical presentation of ICC, many patients either miss the optimal surgical window or experience early postoperative recurrence and metastasis. This poses significant challenges for hepatobiliary surgeons worldwide. Artificial intelligence (AI), as a prominent driver of technological advancement, offers promising new avenues for managing ICC. By leveraging powerful machine learning and deep learning algorithms, AI has demonstrated promising outcomes in ICC diagnosis, particularly in differentiating it from hepatocellular carcinoma, and in predicting critical prognostic factors such as early recurrence, lymph node metastasis, and microvascular invasion. These innovations can support clinical decision-making and ultimately improve patient outcomes. Future efforts should prioritize robust clinical studies evaluating the effectiveness of AI in ICC management.