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Predicting intrahepatic recurrence of colorectal cancer liver metastases after curative hepatectomy using a machine learning model with data integration of ultrasound radiomics and clinicopathological parameters.

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Title: Predicting intrahepatic recurrence of colorectal cancer liver metastases after curative hepatectomy using a machine learning model with data integration of ultrasound radiomics and clinicopathological parameters.
Authors: Hu, Ting1 (AUTHOR), Liu, Zhong2 (AUTHOR), Kuang, Pengpeng3 (AUTHOR), Li, Yunyun4,5 (AUTHOR), Kong, Weixuan6 (AUTHOR), Zheng, Wei6 (AUTHOR), Li, Jianjun1 (AUTHOR), Liu, Guangjian4 (AUTHOR), Zhang, Han7 (AUTHOR), Chen, Xin2 (AUTHOR) chenxin@szu.edu.cn, Zou, Ruhai6 (AUTHOR) zourh@sysucc.org.cn
Source: Insights into Imaging. 3/16/2026, Vol. 17 Issue 1, p1-15. 15p.
Database: Academic Search Ultimate
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An: 192346112
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  Data: <searchLink fieldCode="JN" term="%22Insights+into+Imaging%22">Insights into Imaging</searchLink>. 3/16/2026, Vol. 17 Issue 1, p1-15. 15p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=192346112
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        Value: 10.1186/s13244-026-02227-2
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      – TitleFull: Predicting intrahepatic recurrence of colorectal cancer liver metastases after curative hepatectomy using a machine learning model with data integration of ultrasound radiomics and clinicopathological parameters.
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              M: 03
              Text: 3/16/2026
              Type: published
              Y: 2026
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