https://scholars.lib.ntu.edu.tw/handle/123456789/627338
標題: | End-to-end interstitial fibrosis assessment of kidney biopsies with a machine learning-based model | 作者: | Liu, Zhi-Yong Lin, Chi-Hung Wang, Hsiang-Sheng Wen, Mei-Chin WEI-CHOU LIN Huang, Shun-Chen Tu, Kun-Hua Kuo, Chang-Fu Chen, Tai-Di |
關鍵字: | interstitial fibrosis; machine learning; reliability; reproducibility; whole-slide imaging | 公開日期: | 19-十月-2022 | 出版社: | OXFORD UNIV PRESS | 卷: | 37 | 期: | 11 | 起(迄)頁: | 2093 | 來源出版物: | Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association | 摘要: | The extent of interstitial fibrosis in the kidney not only correlates with renal function at the time of biopsy but also predicts future renal outcome. However, its assessment by pathologists lacks good agreement. The aim of this study is to construct a machine learning-based model that enables automatic and reliable assessment of interstitial fibrosis in human kidney biopsies. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/627338 | ISSN: | 0931-0509 | DOI: | 10.1093/ndt/gfac143 |
顯示於: | 病理學科所 |
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