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Cited by in F6Publishing
For: Chen CL, Chen CC, Yu WH, Chen SH, Chang YC, Hsu TI, Hsiao M, Yeh CY, Chen CY. An annotation-free whole-slide training approach to pathological classification of lung cancer types using deep learning. Nat Commun 2021;12:1193. [PMID: 33608558 DOI: 10.1038/s41467-021-21467-y] [Cited by in Crossref: 2] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
Number Citing Articles
1 Yang S, Ling S. An Artificial Intelligence‐Based Motion Trajectory Prediction of Fibrous Matters. Advanced Intelligent Systems 2022;4:2100136. [DOI: 10.1002/aisy.202100136] [Reference Citation Analysis]
2 Chuang WY, Chen CC, Yu WH, Yeh CJ, Chang SH, Ueng SH, Wang TH, Hsueh C, Kuo CF, Yeh CY. Identification of nodal micrometastasis in colorectal cancer using deep learning on annotation-free whole-slide images. Mod Pathol 2021. [PMID: 34103664 DOI: 10.1038/s41379-021-00838-2] [Reference Citation Analysis]
3 Schirris Y, Gavves E, Nederlof I, Horlings HM, Teuwen J. DeepSMILE: Contrastive self-supervised pre-training benefits MSI and HRD classification directly from H&E whole-slide images in colorectal and breast cancer. Medical Image Analysis 2022. [DOI: 10.1016/j.media.2022.102464] [Reference Citation Analysis]
4 Laleh NG, Muti HS, Loeffler CML, Echle A, Saldanha OL, Mahmood F, Lu MY, Trautwein C, Langer R, Dislich B, Buelow RD, Grabsch HI, Brenner H, Chang-claude J, Alwers E, Brinker TJ, Khader F, Truhn D, Gaisa NT, Boor P, Hoffmeister M, Schulz V, Kather JN. Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology. Medical Image Analysis 2022. [DOI: 10.1016/j.media.2022.102474] [Reference Citation Analysis]
5 Liu Z, Liu Y, Zhang W, Hong Y, Meng J, Wang J, Zheng S, Xu X. Deep learning for prediction of hepatocellular carcinoma recurrence after resection or liver transplantation: a discovery and validation study. Hepatol Int. [DOI: 10.1007/s12072-022-10321-y] [Reference Citation Analysis]
6 Chen CL, Chen CC, Yu WH, Chen SH, Chang YC, Hsu TI, Hsiao M, Yeh CY, Chen CY. An annotation-free whole-slide training approach to pathological classification of lung cancer types using deep learning. Nat Commun 2021;12:1193. [PMID: 33608558 DOI: 10.1038/s41467-021-21467-y] [Cited by in Crossref: 2] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
7 Im S, Hyeon J, Rha E, Lee J, Choi HJ, Jung Y, Kim TJ. Classification of Diffuse Glioma Subtype from Clinical-Grade Pathological Images Using Deep Transfer Learning. Sensors (Basel) 2021;21:3500. [PMID: 34067934 DOI: 10.3390/s21103500] [Reference Citation Analysis]
8 Tao Y, Huang X, Tan Y, Wang H, Jiang W, Chen Y, Wang C, Luo J, Liu Z, Gao K, Yang W, Guo M, Tang B, Zhou A, Yao M, Chen T, Cao Y, Luo C, Zhang J. Qualitative Histopathological Classification of Primary Bone Tumors Using Deep Learning: A Pilot Study. Front Oncol 2021;11:735739. [PMID: 34692509 DOI: 10.3389/fonc.2021.735739] [Reference Citation Analysis]
9 Camalan S, Mahmood H, Binol H, Araújo ALD, Santos-Silva AR, Vargas PA, Lopes MA, Khurram SA, Gurcan MN. Convolutional Neural Network-Based Clinical Predictors of Oral Dysplasia: Class Activation Map Analysis of Deep Learning Results. Cancers (Basel) 2021;13:1291. [PMID: 33799466 DOI: 10.3390/cancers13061291] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
10 Zhao K, Wu X, Li Z, Wang Y, Xu Z, Li Y, Wu L, Yao S, Huang Y, Liang C, Liu Z. Prognostic value of a modified Immunoscore in patients with stage I-III resectable colon cancer. Chin J Cancer Res 2021;33:379-90. [PMID: 34321834 DOI: 10.21147/j.issn.1000-9604.2021.03.09] [Reference Citation Analysis]