LEVERAGING MODERN MACHINE LEARNING TOOLS TO PREDICT OUTCOMES OF IN-PATIENT ACUTE KIDNEY INJURY
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Abstract Number
WCN23-0139
Categories
AKI, Electrolytes, Acid-base Disorders, Tropical Diseases, RPGN and Pregnancy
Topic - Chronic Kidney Disease, Hypertension, Diabetes and CVD
Topic - AKI, Electrolytes, Acid-base Disorders, Tropical Diseases, RPGN and Pregnancy
Other AKI
Topic - Kidney Failure (Former ESKD), incl. Dialysis, Transplantation, Conservative Care
Topic - Special Covid-19
Topic - Education
Abstract Title
LEVERAGING MODERN MACHINE LEARNING TOOLS TO PREDICT OUTCOMES OF IN-PATIENT ACUTE KIDNEY INJURY
Co-authors
Selvaskandan, H.(1,2)*;Gaultney, T.(3);Heath, D.(3);Linfoot, S.(4);Xu, G.(2);
ie:
Azwin Z.1, Siti Y.1, John D.2
Institution
(1)University Of Leicester, Cardiovascular Sciences, Leicester, United Kingdom;(2)University Hospitals Of Leicester Nhs Trust, John Walls Renal Unit, Leicester, United Kingdom;(3)Roke, Applied Machine Learning, Romsey, United Kingdom;(4)Ace, Technical Leadership, London, United Kingdom;
E-Poster
https://storage.unitedwebnetwork.com/files/1041/33adbb8af370f69b246570dadab8d46a.pdf
Audio File
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