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1 Ergebnisse
1
Deep Learning Analysis Using 18F-FDG PET/CT to Predict Occu..:
Ming-li Ouyang
;
Rui-xuan Zheng
;
Yi-ran Wang
...
https://www.frontiersin.org/articles/10.3389/fonc.2022.915871/full. , 2022
Link:
https://doi.org/10.3389/fonc.2022.915871
RT Journal T1 <Title>Deep Learning Analysis Using 18F-FDG PET/CT to Predict Occult Lymph Node Metastasis in Patients With Clinical N0 Lung Adenocarcinoma</Title> UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:1ae84253f21143ce9eeeb973cd63ebba&Exemplar=1&LAN=DE A1 Ming-li Ouyang A1 Rui-xuan Zheng A1 Yi-ran Wang A1 Zi-yi Zuo A1 Liu-dan Gu A1 Yu-qian Tian A1 Yu-guo Wei A1 Xiao-ying Huang A1 Kun Tang A1 Liang-xing Wang PB Frontiers Media S.A. YR 2022 K1 positron emission tomography/computed tomography (PET/CT) K1 convolutional neural network K1 lung adenocarcinoma K1 sublobar resection K1 lymph node status K1 Neoplasms. Tumors. Oncology. Including cancer and carcinogens K1 RC254-282 JF https://www.frontiersin.org/articles/10.3389/fonc.2022.915871/full LK http://dx.doi.org/https://doi.org/10.3389/fonc.2022.915871 DO https://doi.org/10.3389/fonc.2022.915871 SF ELIB - SuUB Bremen
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