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Prediction of adverse pathology in prostate cancer using a multimodal deep learning approach based on [18F]PSMA-1007 PET/CT and multiparametric MRI.

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Title: Prediction of adverse pathology in prostate cancer using a multimodal deep learning approach based on [18F]PSMA-1007 PET/CT and multiparametric MRI.
Authors: Lin, Heng1 (AUTHOR), Yao, Fei2 (AUTHOR), Yi, Xinwen1,3 (AUTHOR), Yuan, Yaping1 (AUTHOR), Xu, Jian4 (AUTHOR), Chen, Lixuan4 (AUTHOR), Wang, Hongyan4 (AUTHOR), Zhuang, Yuandi2 (AUTHOR), Lin, Qi5 (AUTHOR), Xue, Yingnan2 (AUTHOR), Yang, Yunjun4 (AUTHOR) yyjunjim@163.com, Pan, Zhifang1 (AUTHOR) panzhifang@wmu.edu.cn
Source: European Journal of Nuclear Medicine & Molecular Imaging. Jul2025, Vol. 52 Issue 8, p2814-2825. 12p.
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  Data: <searchLink fieldCode="JN" term="%22European+Journal+of+Nuclear+Medicine+%26+Molecular+Imaging%22">European Journal of Nuclear Medicine & Molecular Imaging</searchLink>. Jul2025, Vol. 52 Issue 8, p2814-2825. 12p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=185941776
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        Value: 10.1007/s00259-025-07134-0
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      – TitleFull: Prediction of adverse pathology in prostate cancer using a multimodal deep learning approach based on [18F]PSMA-1007 PET/CT and multiparametric MRI.
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              M: 07
              Text: Jul2025
              Type: published
              Y: 2025
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