Global trends in artificial intelligence applications in liver disease over seventeen years

Table 5 The top ten most cited articles related to artificial intelligence in the field of liver disease

Title	Journals	First author	Year	Citations
Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries	CA Cancer J Clin	Freddie Bray	2018	148
Deep Learning with Convolutional Neural Network for Differentiation of Liver Masses at Dynamic Contrast-enhanced CT: A Preliminary Study	Radiology	Koichiro Yasaka	2018	128
EASL Clinical Practice Guidelines: Management of hepatocellular carcinoma	J Hepatol	European Association for the Study of the Liver	2018	117
Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries	CA Cancer J Clin	Hyuna Sung	2021	112
Diagnosis, Staging, and Management of Hepatocellular Carcinoma: 2018 Practice Guidance by the American Association for the Study of Liver Diseases	Hepatology	Jorge A Marrero	2018	109
AASLD guidelines for the treatment of hepatocellular carcinoma	Hepatology	Julie K Heimbach	2018	91
Radiomics: Images Are More than Pictures, They Are Data	Radiology	Robert J Gillies	2016	89
Radiomic analysis of contrast-enhanced CT predicts microvascular invasion and outcome in hepatocellular carcinoma	J Hepatol	Xun Xu	2019	88
Deep learning Radiomics of shear wave elastography significantly improved diagnostic performance for assessing liver fibrosis in chronic hepatitis B: A prospective multicenter study	Gut	Kun Wang	2019	85
A survey on deep learning in medical image analysis	Med Image Anal	Geert Litjens	2017	78