Literature DB >> 31200978

Machine Learning in Glomerular Diseases: Promise for Precision Medicine.

Girish N Nadkarni1, Kumardeep Chaudhary2, Steven G Coca3.   

Abstract

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Mesh：

Year:  2019        PMID： 31200978     DOI： 10.1053/j.ajkd.2019.04.011

Source DB:  PubMed          Journal:  Am J Kidney Dis        ISSN： 0272-6386            Impact factor:   8.860


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  3 in total

1.  Prediction of prognosis in immunoglobulin a nephropathy patients with focal crescent by machine learning.

Authors:  Xuefei Lin; Yongfang Liu; Yizhen Chen; Xiaodan Huang; Jundu Li; Yuansheng Hou; Miaoying Shen; Zaoqiang Lin; Ronglin Zhang; Haifeng Yang; Songlin Hong; Xusheng Liu; Chuan Zou
Journal:  PLoS One       Date:  2022-03-09       Impact factor: 3.240

2.  Glomerular disease classification and lesion identification by machine learning.

Authors:  Cheng-Kun Yang; Ching-Yi Lee; Hsiang-Sheng Wang; Shun-Chen Huang; Peir-In Liang; Jung-Sheng Chen; Chang-Fu Kuo; Kun-Hua Tu; Chao-Yuan Yeh; Tai-Di Chen
Journal:  Biomed J       Date:  2021-09-08       Impact factor: 7.892

Review 3.  Artificial Intelligence-Assisted Renal Pathology: Advances and Prospects.

Authors:  Yiqin Wang; Qiong Wen; Luhua Jin; Wei Chen
Journal:  J Clin Med       Date:  2022-08-22       Impact factor: 4.964
  3 in total

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