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Cited by in F6Publishing
For: Nishida N, Yamakawa M, Shiina T, Mekada Y, Nishida M, Sakamoto N, Nishimura T, Iijima H, Hirai T, Takahashi K, Sato M, Tateishi R, Ogawa M, Mori H, Kitano M, Toyoda H, Ogawa C, Kudo M; JSUM A. I. investigators. Artificial intelligence (AI) models for the ultrasonographic diagnosis of liver tumors and comparison of diagnostic accuracies between AI and human experts. J Gastroenterol. [DOI: 10.1007/s00535-022-01849-9] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
Number Citing Articles
1 Zhang WB, Hou SZ, Chen YL, Mao F, Dong Y, Chen JG, Wang WP. Deep Learning for Approaching Hepatocellular Carcinoma Ultrasound Screening Dilemma: Identification of α-Fetoprotein-Negative Hepatocellular Carcinoma From Focal Liver Lesion Found in High-Risk Patients. Front Oncol 2022;12:862297. [PMID: 35720017 DOI: 10.3389/fonc.2022.862297] [Reference Citation Analysis]