Omics and Artificial Intelligence in Kidney Diseases

被引:6
|
作者
Grobe, Nadja [1 ,4 ]
Scheiber, Josef [2 ]
Zhang, Hanjie [1 ]
Garbe, Christian [3 ]
Wang, Xiaoling [1 ]
机构
[1] Renal Res Inst, New York, NY USA
[2] Biovariance GmbH, Waldsassen, Germany
[3] Frankfurter Innovationszentrum Biotechnol, Frankfurt, Germany
[4] 315 East 62nd St, 3rd Floor, New York, NY 10065 USA
来源
ADVANCES IN KIDNEY DISEASE AND HEALTH | 2023年 / 30卷 / 01期
关键词
Machine learning; Computational; Modeling; Stratification; Prediction; Artificial Intelligence; PERITONEAL-DIALYSIS EFFLUENT; BIOMARKERS;
D O I
10.1053/j.akdh.2022.11.005
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Omics applications in nephrology may have relevance in the future to improve clinical care of kidney disease patients. In a short term, patients will benefit from specific measurement and computational analyses around biomarkers identified at various omics-levels. In mid term and long term, these approaches will need to be integrated into a holistic representation of the kidney and all its influencing factors for individualized patient care. Research demonstrates robust data to justify the application of omics for better understanding, risk stratification, and individualized treatment of kidney disease patients. Despite these ad-vances in the research setting, there is still a lack of evidence showing the combination of omics technologies with artificial in-telligence and its application in clinical diagnostics and care of patients with kidney disease. Q 2022 The Authors. Published by Elsevier Inc. on behalf of the National Kidney Foundation, Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:47 / 52
页数:6
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