Artificial Intelligence and Dialysis
Author:
Publisher
S. Karger AG
Subject
Materials Chemistry
Reference6 articles.
1. Hueso M, Navarro E, Sandoval D, Cruzado JM. Progress in the development and challenges for the use of artificial kidneys and wearable dialysis devices. Kidney Dis. DOI: 10.1159/000492932.
2. Vellido A. Societal issues concerning the application of artificial intelligence in medicine. Kidney Dis. DOI: 10.1159/000492428.
3. Jonsson A. Deep reinforcement learning in medicine. Kidney Dis. DOI: 10.1159/000492670.
4. Ribas Ripoll V, Vellido A. Blood pressure assessment with differential pulse transit time and deep learning: a proof of concept. Kidney Dis. DOI: 10.1159/000493478.
5. Barbieri C, Cattinelli I, Neri L, Mari F, Ramos R, Brancaccio D, et al. Development of an artificial intelligence model to guide the management of blood pressure, fluid volume and dialysis dose in end-stage kidney disease patients: proof of concept and first clinical assessment. Kidney Dis. DOI: 10.1159/493479.
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1. Is generative artificial intelligence the next step toward a personalized hemodialysis?;Revista de investigaci�n Cl�nica;2023-12-20
2. Feature Selection for Intradialytic Blood Pressure Value Prediction Using GRU-based Method Under RFECV algorithm;2021 9th International Conference on Orange Technology (ICOT);2021-12-16
3. Prediction of the Mortality Risk in Peritoneal Dialysis Patients using Machine Learning Models: A Nation-wide Prospective Cohort in Korea;Scientific Reports;2020-05-04
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