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肾脏疾病中的组学与人工智能

Omics and Artificial Intelligence in Kidney Diseases.

作者信息

Grobe Nadja, Scheiber Josef, Zhang Hanjie, Garbe Christian, Wang Xiaoling

机构信息

Renal Research Institute, New York, NY.

BioVariance GmbH, Waldsassen, Germany.

出版信息

Adv Kidney Dis Health. 2023 Jan;30(1):47-52. doi: 10.1053/j.akdh.2022.11.005.

Abstract

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 advances in the research setting, there is still a lack of evidence showing the combination of omics technologies with artificial intelligence and its application in clinical diagnostics and care of patients with kidney disease.

摘要

组学在肾脏病学中的应用未来可能与改善肾病患者的临床护理相关。短期内,患者将受益于围绕在各种组学水平上鉴定出的生物标志物进行的特定测量和计算分析。从中期和长期来看,这些方法需要整合到肾脏及其所有影响因素的整体表征中,以实现个性化的患者护理。研究表明有充分的数据证明应用组学有助于更好地理解、风险分层以及对肾病患者进行个体化治疗。尽管在研究领域取得了这些进展,但仍缺乏证据表明组学技术与人工智能的结合及其在肾病患者临床诊断和护理中的应用。

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