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 |