Deep Learning Analysis Using 18F-FDG PET/CT to Predict Occult Lymph Node Metastasis in Patients With Clinical N0 Lung Adenocarcinoma.
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| Title: | Deep Learning Analysis Using 18F-FDG PET/CT to Predict Occult Lymph Node Metastasis in Patients With Clinical N0 Lung Adenocarcinoma. |
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| Authors: | Ouyang ML; Key Laboratory of Heart and Lung, Division of Pulmonary Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China., Zheng RX; Key Laboratory of Heart and Lung, Division of Pulmonary Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China., Wang YR; Department of Medical Engineering, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China., Zuo ZY; Key Laboratory of Heart and Lung, Division of Pulmonary Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China., Gu LD; Key Laboratory of Heart and Lung, Division of Pulmonary Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China., Tian YQ; Key Laboratory of Heart and Lung, Division of Pulmonary Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China., Wei YG; Precision Health Institution, General Electric (GE) Healthcare, Hangzhou, China., Huang XY; Key Laboratory of Heart and Lung, Division of Pulmonary Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China., Tang K; Department of Nuclear Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China., Wang LX; Key Laboratory of Heart and Lung, Division of Pulmonary Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China. |
| Source: | Frontiers in oncology [Front Oncol] 2022 Jul 07; Vol. 12, pp. 915871. Date of Electronic Publication: 2022 Jul 07 (Print Publication: 2022). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Frontiers Research Foundation] Country of Publication: Switzerland NLM ID: 101568867 Publication Model: eCollection Cited Medium: Print ISSN: 2234-943X (Print) Linking ISSN: 2234943X NLM ISO Abbreviation: Front Oncol Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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