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

• 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
• Institution: National University of Singapore

10.1186/s12882-019-1206-4