Predicting chronic kidney disease progression using small pathology datasets and explainable machine learning models
Version 2 2024-09-17, 02:36
Version 1 2024-09-16, 00:52
journal contribution
posted on 2024-09-17, 02:36 authored by Sandeep Reddy, Supriya Roy, Kay Weng Choy, Sourav Sharma, Karen M Dwyer, Chaitanya Manapragada, Zane Miller, Joy Cheon, Bahareh NakisaBahareh NakisaPredicting chronic kidney disease progression using small pathology datasets and explainable machine learning models
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Journal
Computer Methods and Programs in Biomedicine UpdateVolume
6Article number
100160Pagination
1-11Location
Amsterdam, The NetherlandsPublisher DOI
Open access
- Yes
ISSN
2666-9900eISSN
2666-9900Language
enPublication classification
C1 Refereed article in a scholarly journalPublisher
ElsevierPublication URL
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Keywords
Kidney DiseaseMachine Learning and Artificial IntelligenceNetworking and Information Technology R&D (NITRD)Renal and urogenital4.1 Discovery and preclinical testing of markers and technologiesChronic kidney disease predictionExplainable machine learningTransfer learningShapley additive exPlanationsCounterfactual analysis
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