Revisiting artificial intelligence diagnosis of hepatocellular carcinoma with DIKWH framework - Shen, Xiaomin; Wu, Jinxin; Su, Junwei; Yao, Zhenyu; Huang, Wei; Zhang, Li; Jiang, Yiheng; Yu, Wei; Li, Zhao (Frontiers in Genetics, 2023)
Hepatocellular carcinoma (HCC) is a type of malignancy, causing high morbidity and fatality rate. The traditional diagnostic methods for HCC are mainly based on clinical presentation, methotrexate, imaging features and histopathology. With the rapid development of artificial intelligence (AI), which is increasingly used in the diagnosis, treatment, and prognosis prediction of HCC, an automated approach to HCC status classification is promising. Artificial intelligence integrates labeled clinical data, trains on new data of the same type and performs interpretation tasks. Several studies have shown that AI techniques can help clinicians and radiologists to be more efficient and reduce the rate of misdiagnosis. However, the breadth of coverage of AI technologies leads us to respond to different specific problems in different situations generating exactly which type of AI technology should be more preferred, which not only can significantly reduce the time to choose a tool in healthcare by solving this kind challenge, but also is a tool that can provide more precise and personalized solutions for different specific problems. In our review research work, we summarize the existing research works, compare and classify the main results of these researches according to a specified DIKW(Data Information Knowledge Wisdom) framework system.