Advancing EGFR mutation subtypes prediction in NSCLC by combining 3D pretrained ConvNeXt, radiomics, and clinical features.
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| Title: | Advancing EGFR mutation subtypes prediction in NSCLC by combining 3D pretrained ConvNeXt, radiomics, and clinical features. |
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| Authors: | Hao P; Department of Diagnostic Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China., Yu Y; AIgorithm Department, Dianei Technology, Shanghai, China., Huang CT; Department of Diagnostic Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China., Zhou F; Department of Diagnostic Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China., Xu YK; Department of Diagnostic Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China., Yang J; AIgorithm Department, Dianei Technology, Shanghai, China.; Computer Vision Laboratory, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland., Xu J; Department of Hematology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China. |
| Source: | Frontiers in oncology [Front Oncol] 2024 Nov 15; Vol. 14, pp. 1464555. Date of Electronic Publication: 2024 Nov 15 (Print Publication: 2024). |
| 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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