A neural network approach to glomerular filtration rate estimation: a single-centre retrospective audit

Although the model is not sufficiently sensitive to predict the optimum time-sample point for a single-sample regime, this work can serve as a proof of concept for UK-specific NN GFR models.

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Publication Details

Journal
Nuclear Medicine Communications
Published
2025-04-07
DOI
https://doi.org/10.1097/mnm.0000000000001982
Primary Topic
Chronic Kidney Disease and Diabetes
Type
article
Field-Weighted Citation Impact
0.00
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article

A neural network approach to glomerular filtration rate estimation: a single-centre retrospective audit

John Johnson, Richard Meades, Nathan Dickinson
Nuclear Medicine Communications
Chronic Kidney Disease and Diabetes
article

A neural network approach to glomerular filtration rate estimation: a single-centre retrospective audit

John Johnson, Richard Meades, Nathan Dickinson
article en

Abstract

Although the model is not sufficiently sensitive to predict the optimum time-sample point for a single-sample regime, this work can serve as a proof of concept for UK-specific NN GFR models.

Nuclear Medicine CommunicationsVol. 46(7)
Royal Free London NHS Foundation Trust (GB), University Hospitals of Leicester NHS Trust (GB), University of Oxford (GB)
Good health and well-being
Openalex Percentile: Top 91%
Chronic Kidney Disease and Diabetes
DOIOpen Access PDFOpenAlex
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