Artificial intelligence approaches to improve kidney care-Reference-Cited by-同舟云学术

Artificial intelligence approaches to improve kidney care

Published:2019-12-23 Issue:2 Volume:16 Page:71-72
ISSN:1759-5061
Container-title:Nature Reviews Nephrology
language:en
Short-container-title:Nat Rev Nephrol

Author:

Rashidi Parisa^ORCID,Bihorac Azra^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Nephrology

Link

http://www.nature.com/articles/s41581-019-0243-3.pdf

Reference10 articles.

1. United States Department of Health and Human Services. Advancing American kidney health. HHS https://aspe.hhs.gov/system/files/pdf/262046/AdvancingAmericanKidneyHealth.pdf (2019).

2. Vinyals, O. et al. Grandmaster level in StarCraft II using multi-agent reinforcement learning. Nature 575, 350–354 (2019).

3. American Medical Association. Augmented intelligence in health care. AMA https://www.ama-assn.org/system/files/2019-08/ai-2018-board-policy-summary.pdf (2019).

4. Al-Jaghbeer, M. et al. Clinical decision support for in-hospital AKI. J. Am. Soc. Nephrol. 29, 654–660 (2018).

5. Tomašev, N. et al. A clinically applicable approach to continuous prediction of future acute kidney injury. Nature 572, 116–119 (2019).

Cited by 40 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Personalized prediction of intradialytic hypotension in clinical practice: Development and evaluation of a novel AI dashboard incorporating risk factors from previous and current dialysis sessions;International Journal of Medical Informatics;2024-10

2. Prediction of hypotension during haemodialysis through data analytics and machine learning;Journal of Kidney Care;2024-09-02

3. Decoding depression: a comprehensive multi-cohort exploration of blood DNA methylation using machine learning and deep learning approaches;Translational Psychiatry;2024-07-15

4. Analysis of the performance of the CorneAI for iOS in the classification of corneal diseases and cataracts based on journal photographs;Scientific Reports;2024-07-05

5. A simple machine learning model for the prediction of acute kidney injury following noncardiac surgery in geriatric patients: a prospective cohort study;BMC Geriatrics;2024-06-25