摘要
In recent years,significant advances have been achieved in liver cancer management with the development of artificial intelligence(AI).AI-based pathological analysis can extract crucial information from whole slide images to assist clinicians in all aspects from diagnosis to prognosis and molecular profiling.However,AI techniques have a“black box”nature,which means that interpretability is of utmost importance because it is key to ensuring the reliability of the methods and building trust among clinicians for actual clinical implementation.In this paper,we provide an overview of current technical advancements in the AI-based pathological analysis of liver cancer,and delve into the strategies used in recent studies to unravel the“black box”of AI's decision-making process.
出处
《iLIVER》
2024年第1期82-89,共8页
国际肝胆健康（英文）
基金
supported by the National Natural Science Foundation of China(Nos 81961128025 and 82273187)
the Research Projects from the Science and Technology Commission of Shanghai Municipality(Nos 21JC1401200 and 20JC1418900)
the Natural Science Foundation of Fujian Province(No.2023J05292).
