Electronic health records accurately predict renal replacement therapy in acute kidney injury

10.1186/s12882-019-1206-4

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Bibliographic Details
Main Authors:	Low, Sanmay, Vathsala, Anantharaman, Murali, Tanusya Murali, Pang, Long, MacLaren, Graeme, Ng, Wan-Ying, Haroon, Sabrina, Mukhopadhyay, Amartya, Lim, Shir-Lynn, Tan, Bee-Hong, Lau, Titus, Chua, Horng-Ruey
Other Authors:	MEDICINE
Format:	Article
Language:	English
Published:	BMC 2019
Subjects:	Science & Technology Life Sciences & Biomedicine Urology & Nephrology Acute kidney injury Decision support techniques Electronic health records Epidemiology Mortality Outcomes and process assessment Renal replacement therapy CRITICALLY-ILL PATIENTS DIALYSIS AKI MULTICENTER INTENSITY PROGNOSIS FAILURE DEATH SCORE MODEL
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/155324
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Institution:	National University of Singapore
Language:	English

id	sg-nus-scholar.10635-155324
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spelling	sg-nus-scholar.10635-1553242024-04-25T02:36:15Z Electronic health records accurately predict renal replacement therapy in acute kidney injury Low, Sanmay Vathsala, Anantharaman Murali, Tanusya Murali Pang, Long MacLaren, Graeme Ng, Wan-Ying Haroon, Sabrina Mukhopadhyay, Amartya Lim, Shir-Lynn Tan, Bee-Hong Lau, Titus Chua, Horng-Ruey MEDICINE SAW SWEE HOCK SCHOOL OF PUBLIC HEALTH SURGERY ANAESTHESIA Science & Technology Life Sciences & Biomedicine Urology & Nephrology Acute kidney injury Decision support techniques Electronic health records Epidemiology Mortality Outcomes and process assessment Renal replacement therapy CRITICALLY-ILL PATIENTS DIALYSIS AKI MULTICENTER INTENSITY PROGNOSIS FAILURE DEATH SCORE MODEL 10.1186/s12882-019-1206-4 BMC NEPHROLOGY 20 1 2019-06-07T01:48:39Z 2019-06-07T01:48:39Z 2019-01-31 2019-06-03T15:42:23Z Article Low, Sanmay, Vathsala, Anantharaman, Murali, Tanusya Murali, Pang, Long, MacLaren, Graeme, Ng, Wan-Ying, Haroon, Sabrina, Mukhopadhyay, Amartya, Lim, Shir-Lynn, Tan, Bee-Hong, Lau, Titus, Chua, Horng-Ruey (2019-01-31). Electronic health records accurately predict renal replacement therapy in acute kidney injury. BMC NEPHROLOGY 20 (1). ScholarBank@NUS Repository. https://doi.org/10.1186/s12882-019-1206-4 1471-2369 1471-2369 https://scholarbank.nus.edu.sg/handle/10635/155324 en BMC Elements
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
language	English
topic	Science & Technology Life Sciences & Biomedicine Urology & Nephrology Acute kidney injury Decision support techniques Electronic health records Epidemiology Mortality Outcomes and process assessment Renal replacement therapy CRITICALLY-ILL PATIENTS DIALYSIS AKI MULTICENTER INTENSITY PROGNOSIS FAILURE DEATH SCORE MODEL
spellingShingle	Science & Technology Life Sciences & Biomedicine Urology & Nephrology Acute kidney injury Decision support techniques Electronic health records Epidemiology Mortality Outcomes and process assessment Renal replacement therapy CRITICALLY-ILL PATIENTS DIALYSIS AKI MULTICENTER INTENSITY PROGNOSIS FAILURE DEATH SCORE MODEL Low, Sanmay Vathsala, Anantharaman Murali, Tanusya Murali Pang, Long MacLaren, Graeme Ng, Wan-Ying Haroon, Sabrina Mukhopadhyay, Amartya Lim, Shir-Lynn Tan, Bee-Hong Lau, Titus Chua, Horng-Ruey Electronic health records accurately predict renal replacement therapy in acute kidney injury
description	10.1186/s12882-019-1206-4
author2	MEDICINE
author_facet	MEDICINE Low, Sanmay Vathsala, Anantharaman Murali, Tanusya Murali Pang, Long MacLaren, Graeme Ng, Wan-Ying Haroon, Sabrina Mukhopadhyay, Amartya Lim, Shir-Lynn Tan, Bee-Hong Lau, Titus Chua, Horng-Ruey
format	Article
author	Low, Sanmay Vathsala, Anantharaman Murali, Tanusya Murali Pang, Long MacLaren, Graeme Ng, Wan-Ying Haroon, Sabrina Mukhopadhyay, Amartya Lim, Shir-Lynn Tan, Bee-Hong Lau, Titus Chua, Horng-Ruey
author_sort	Low, Sanmay
title	Electronic health records accurately predict renal replacement therapy in acute kidney injury
title_short	Electronic health records accurately predict renal replacement therapy in acute kidney injury
title_full	Electronic health records accurately predict renal replacement therapy in acute kidney injury
title_fullStr	Electronic health records accurately predict renal replacement therapy in acute kidney injury
title_full_unstemmed	Electronic health records accurately predict renal replacement therapy in acute kidney injury
title_sort	electronic health records accurately predict renal replacement therapy in acute kidney injury
publisher	BMC
publishDate	2019
url	https://scholarbank.nus.edu.sg/handle/10635/155324
_version_	1800913621659680768

Electronic health records accurately predict renal replacement therapy in acute kidney injury

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