Zhao K - Search Results

1

Multiple Level CT Radiomics Features Preoperatively Predict Lymph Node Metastasis in Esophageal Cancer: A Multicentre Retrospective Study.

Wu L, Yang X, Cao W, Zhao K, Li W, Ye W, Chen X, Zhou Z, Liu Z, Liang C. Wu L, et al. Among authors: zhao k. Front Oncol. 2020 Jan 21;9:1548. doi: 10.3389/fonc.2019.01548. eCollection 2019. Front Oncol. 2020. PMID: 32039021 Free PMC article.

2

Validation of Breast Cancer Models for Predicting the Nonsentinel Lymph Node Metastasis After a Positive Sentinel Lymph Node Biopsy in a Chinese Population.

Wu P, Zhao K, Liang Y, Ye W, Liu Z, Liang C. Wu P, et al. Among authors: zhao k. Technol Cancer Res Treat. 2018 Jan 1;17:1533033818785032. doi: 10.1177/1533033818785032. Technol Cancer Res Treat. 2018. PMID: 30033828 Free PMC article.

3

Radiomics approach for preoperative identification of stages I-II and III-IV of esophageal cancer.

Wu L, Wang C, Tan X, Cheng Z, Zhao K, Yan L, Liang Y, Liu Z, Liang C. Wu L, et al. Among authors: zhao k. Chin J Cancer Res. 2018 Aug;30(4):396-405. doi: 10.21147/j.issn.1000-9604.2018.04.02. Chin J Cancer Res. 2018. PMID: 30210219 Free PMC article.

4

Deep Learning Signature Based on Staging CT for Preoperative Prediction of Sentinel Lymph Node Metastasis in Breast Cancer.

Yang X, Wu L, Ye W, Zhao K, Wang Y, Liu W, Li J, Li H, Liu Z, Liang C. Yang X, et al. Among authors: zhao k. Acad Radiol. 2020 Sep;27(9):1226-1233. doi: 10.1016/j.acra.2019.11.007. Epub 2019 Dec 7. Acad Radiol. 2020. PMID: 31818648

5

Deep Learning Features Improve the Performance of a Radiomics Signature for Predicting KRAS Status in Patients with Colorectal Cancer.

Wu X, Li Y, Chen X, Huang Y, He L, Zhao K, Huang X, Zhang W, Huang Y, Li Y, Dong M, Huang J, Xia T, Liang C, Liu Z. Wu X, et al. Among authors: zhao k. Acad Radiol. 2020 Nov;27(11):e254-e262. doi: 10.1016/j.acra.2019.12.007. Epub 2020 Jan 23. Acad Radiol. 2020. PMID: 31982342

6

Normalization of multicenter CT radiomics by a generative adversarial network method.

Li Y, Han G, Wu X, Li ZH, Zhao K, Zhang Z, Liu Z, Liang C. Li Y, et al. Among authors: zhao k. Phys Med Biol. 2021 Feb 25;66(5). doi: 10.1088/1361-6560/ab8319. Phys Med Biol. 2021. PMID: 32209747

7

Evaluation of human epidermal growth factor receptor 2 status of breast cancer using preoperative multidetector computed tomography with deep learning and handcrafted radiomics features.

Yang X, Wu L, Zhao K, Ye W, Liu W, Wang Y, Li J, Li H, Huang X, Zhang W, Huang Y, Chen X, Yao S, Liu Z, Liang C. Yang X, et al. Among authors: zhao k. Chin J Cancer Res. 2020 Apr;32(2):175-185. doi: 10.21147/j.issn.1000-9604.2020.02.05. Chin J Cancer Res. 2020. PMID: 32410795 Free PMC article.

8

Predicting treatment response to neoadjuvant chemoradiotherapy in local advanced rectal cancer by biopsy digital pathology image features.

Zhang F, Yao S, Li Z, Liang C, Zhao K, Huang Y, Gao Y, Qu J, Li Z, Liu Z. Zhang F, et al. Among authors: zhao k. Clin Transl Med. 2020 Jun;10(2):e110. doi: 10.1002/ctm2.110. Epub 2020 Jun 28. Clin Transl Med. 2020. PMID: 32594660 Free PMC article.

9

Artificial intelligence quantified tumour-stroma ratio is an independent predictor for overall survival in resectable colorectal cancer.

Zhao K, Li Z, Yao S, Wang Y, Wu X, Xu Z, Wu L, Huang Y, Liang C, Liu Z. Zhao K, et al. EBioMedicine. 2020 Nov;61:103054. doi: 10.1016/j.ebiom.2020.103054. Epub 2020 Oct 8. EBioMedicine. 2020. PMID: 33039706 Free PMC article.

10

Hist-Immune signature: a prognostic factor in colorectal cancer using immunohistochemical slide image analysis.

Zhao K, Li Z, Li Y, Yao S, Huang Y, Wang Y, Zhang F, Wu L, Chen X, Liang C, Liu Z. Zhao K, et al. Oncoimmunology. 2020 Oct 30;9(1):1841935. doi: 10.1080/2162402X.2020.1841935. Oncoimmunology. 2020. PMID: 33194320 Free PMC article.

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