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Get Free AccessThe performance of the AI models surpassed that of human experts in the four-class discrimination and benign and malignant discrimination of liver tumors. Thus, the AI models can help prevent human errors in US diagnosis.
Naoshi Nishida, Makoto Yamakawa, Tsuyoshi Shiina, Yoshito Mekada, Mutsumi Nishida, Naoya Sakamoto, Takashi Nishimura, Hiroko Iijima, Toshiko Hirai, Ken Takahashi, Masaya Sato, Ryosuke Tateishi, Masahiro Ogawa, Hideaki Mori, Masayuki Kitano, Hidenori Toyoda, Chikara Ogawa, Masatoshi Kudo (2022). Artificial intelligence (AI) models for the ultrasonographic diagnosis of liver tumors and comparison of diagnostic accuracies between AI and human experts. , 57(4), DOI: https://doi.org/10.1007/s00535-022-01849-9.
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Type
Article
Year
2022
Authors
18
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1007/s00535-022-01849-9
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