Utilization of Deep Learning for Subphenotype Identification in Sepsis-Associated Acute Kidney Injury.

Kumardeep ChaudharyAkhil VaidÁine DuffyIshan ParanjpeSuraj K JaladankiManish ParanjpeKipp W Johnson Avantee Gokhale Pattharawin Pattharanitima Kinsuk Chauhan Ross O'Hagan Tielman T Van Vleck Steven G CocaRichard CooperBenjamin Scott GlicksbergErwin P BottingerLili ChanGirish N Nadkarni

Published in: Clinical journal of the American Society of Nephrology : CJASN (2020)

Utilizing routinely collected laboratory variables, vital signs, and comorbidities, we were able to identify three distinct subphenotypes of sepsis-associated AKI with differing outcomes.

Keyphrases

acute kidney injury
cardiac surgery
deep learning
septic shock
artificial intelligence
machine learning
convolutional neural network
type diabetes
metabolic syndrome
skeletal muscle