Pan X - Search Results

1

The Clinical Value of Explainable Deep Learning for Diagnosing Fungal Keratitis Using in vivo Confocal Microscopy Images.

Xu F, Jiang L, He W, Huang G, Hong Y, Tang F, Lv J, Lin Y, Qin Y, Lan R, Pan X, Zeng S, Li M, Chen Q, Tang N. Xu F, et al. Among authors: pan x. Front Med (Lausanne). 2021 Dec 14;8:797616. doi: 10.3389/fmed.2021.797616. eCollection 2021. Front Med (Lausanne). 2021. PMID: 34970572 Free PMC article.

2

Meta multi-task nuclei segmentation with fewer training samples.

Han C, Yao H, Zhao B, Li Z, Shi Z, Wu L, Chen X, Qu J, Zhao K, Lan R, Liang C, Pan X, Liu Z. Han C, et al. Among authors: pan x. Med Image Anal. 2022 Aug;80:102481. doi: 10.1016/j.media.2022.102481. Epub 2022 May 18. Med Image Anal. 2022. PMID: 35653901

3

An artificial intelligence approach to classify pathogenic fungal genera of fungal keratitis using corneal confocal microscopy images.

Tang N, Huang G, Lei D, Jiang L, Chen Q, He W, Tang F, Hong Y, Lv J, Qin Y, Lin Y, Lan Q, Qin Y, Lan R, Pan X, Li M, Xu F, Lu P. Tang N, et al. Among authors: pan x. Int Ophthalmol. 2023 Jul;43(7):2203-2214. doi: 10.1007/s10792-022-02616-8. Epub 2023 Jan 3. Int Ophthalmol. 2023. PMID: 36595127

4

A Hybrid System for Automatic Identification of Corneal Layers on In Vivo Confocal Microscopy Images.

Tang N, Huang G, Lei D, Jiang L, Chen Q, He W, Tang F, Hong Y, Lv J, Qin Y, Lin Y, Lan Q, Qin Y, Lan R, Pan X, Li M, Xu F, Lu P. Tang N, et al. Among authors: pan x. Transl Vis Sci Technol. 2023 Apr 3;12(4):8. doi: 10.1167/tvst.12.4.8. Transl Vis Sci Technol. 2023. PMID: 37026984 Free PMC article.

5

SMILE: Cost-sensitive multi-task learning for nuclear segmentation and classification with imbalanced annotations.

Pan X, Cheng J, Hou F, Lan R, Lu C, Li L, Feng Z, Wang H, Liang C, Liu Z, Chen X, Han C, Liu Z. Pan X, et al. Med Image Anal. 2023 Aug;88:102867. doi: 10.1016/j.media.2023.102867. Epub 2023 Jun 12. Med Image Anal. 2023. PMID: 37348167

6

Automated whole-slide images assessment of immune infiltration in resected non-small-cell lung cancer: towards better risk-stratification.

Lin H, Pan X, Feng Z, Yan L, Hua J, Liang Y, Han C, Xu Z, Wang Y, Wu L, Cui Y, Huang X, Shi Z, Chen X, Chen X, Zhang Q, Liang C, Zhao K, Li Z, Liu Z. Lin H, et al. Among authors: pan x. J Transl Med. 2022 Jun 7;20(1):261. doi: 10.1186/s12967-022-03458-9. J Transl Med. 2022. PMID: 35672787 Free PMC article.

7

Multi-scale pathology image texture signature is a prognostic factor for resectable lung adenocarcinoma: a multi-center, retrospective study.

Wang Y, Pan X, Lin H, Han C, An Y, Qiu B, Feng Z, Huang X, Xu Z, Shi Z, Chen X, Li B, Yan L, Lu C, Li Z, Cui Y, Liu Z, Liu Z. Wang Y, et al. Among authors: pan x. J Transl Med. 2022 Dec 14;20(1):595. doi: 10.1186/s12967-022-03777-x. J Transl Med. 2022. PMID: 36517832 Free PMC article.

8

Histopathological Tissue Segmentation of Lung Cancer with Bilinear CNN and Soft Attention.

Xu R, Wang Z, Liu Z, Han C, Yan L, Lin H, Xu Z, Feng Z, Liang C, Chen X, Pan X, Liu Z. Xu R, et al. Among authors: pan x. Biomed Res Int. 2022 Jul 7;2022:7966553. doi: 10.1155/2022/7966553. eCollection 2022. Biomed Res Int. 2022. PMID: 35845926 Free PMC article.

9

Computerized tumor-infiltrating lymphocytes density score predicts survival of patients with resectable lung adenocarcinoma.

Pan X, Lin H, Han C, Feng Z, Wang Y, Lin J, Qiu B, Yan L, Li B, Xu Z, Wang Z, Zhao K, Liu Z, Liang C, Chen X, Li Z, Cui Y, Lu C, Liu Z. Pan X, et al. iScience. 2022 Nov 16;25(12):105605. doi: 10.1016/j.isci.2022.105605. eCollection 2022 Dec 22. iScience. 2022. PMID: 36505920 Free PMC article.

10

Computerized tertiary lymphoid structures density on H&E-images is a prognostic biomarker in resectable lung adenocarcinoma.

Wang Y, Lin H, Yao N, Chen X, Qiu B, Cui Y, Liu Y, Li B, Han C, Li Z, Zhao W, Wang Z, Pan X, Lu C, Liu J, Liu Z, Liu Z. Wang Y, et al. Among authors: pan x. iScience. 2023 Aug 16;26(9):107635. doi: 10.1016/j.isci.2023.107635. eCollection 2023 Sep 15. iScience. 2023. PMID: 37664636 Free PMC article.

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