Omics and Artificial Intelligence in Kidney Diseases.
Artificial Intelligence
Computational
Machine learning
Modeling
Prediction
Stratification
Journal
Advances in kidney disease and health
ISSN: 2949-8139
Titre abrégé: Adv Kidney Dis Health
Pays: United States
ID NLM: 9918523075306676
Informations de publication
Date de publication:
01 2023
01 2023
Historique:
received:
06
10
2022
revised:
28
10
2022
accepted:
16
11
2022
entrez:
1
2
2023
pubmed:
2
2
2023
medline:
4
2
2023
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 36723282
pii: S2949-8139(22)00006-4
doi: 10.1053/j.akdh.2022.11.005
pii:
doi:
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
47-52Informations de copyright
Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.