Low Predictability of Readmissions and Death Using Machine Learning in Cirrhosis.

Abstract

Authors

• Chang Hu
  Department of Critical Care Medicine, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.
• Vikram Anjur
  Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
• Krishnakant Saboo
  Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
• K Rajender Reddy
  Department of Medicine, Division of Gastroenterology and Hepatology, University of Pennsylvania, Philadelphia, PA, USA.
• Jacqueline O'Leary
  Dallas VA Medical Center, Dallas, Texas, USA.
• Puneeta Tandon
  Department of Gastroenterology, University of Alberta, Edmonton, AB, Canada.
• Florence Wong
  University of Toronto, Toronto, Ontario, Canada.
• Guadalupe Garcia-Tsao
  Section of Digestive Diseases, Department of Medicine, Yale School of Medicine, New Haven, USA.
• Patrick S Kamath
  Department of Medicine, Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MA, USA.
• Jennifer C Lai
  University of California, San Francisco, California, USA.
• Scott W Biggins
  University of Washington, Seattle, Washington, USA.
• Michael B Fallon
  University of Arizona, Phoenix, Arizona, USA.
• Paul Thuluvath
  Mercy Medical Center, Baltimore, Maryland, USA.
• Ram M Subramanian
  Emory University, Atlanta, Georgia, USA.
• Benedict Maliakkal
  University of Tennessee, Memphis, Tennessee, USA.
• Hugo Vargas
  Mayo Clinic, Phoenix, Arizona, USA.
• Leroy R Thacker
  Virginia Commonwealth University and McGuire VA Medical Center, Richmond, Virginia, USA.
• Ravishankar K Iyer
  Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.
• Jasmohan S Bajaj
  Virginia Commonwealth University and McGuire VA Medical Center, Richmond, Virginia, USA.

Keywords

External Resources