Machine learning for prediction of chronic kidney disease progression: Validation of the Klinrisk model in the CANVAS Program and CREDENCE trial.

Abstract

Authors

• Navdeep Tangri
  Department of Internal Medicine, University of Manitoba, Winnipeg, MB, Canada.
• Thomas W Ferguson
  Department of Internal Medicine, Max Rady College of Medicine, University of Manitoba, Winnipeg, Canada.
• Ryan J Bamforth
  Chronic Disease Innovation Centre, Seven Oaks General Hospital, Winnipeg, Canada.
• Silvia J Leon
  Chronic Disease Innovation Centre, Seven Oaks General Hospital, Winnipeg, Canada.
• Clare Arnott
  The George Institute for Global Health, University of New South Wales, Sydney, Australia.
• Kenneth W Mahaffey
  Stanford Center for Clinical Research, Stanford University School of Medicine, Stanford, CA.
• Sradha Kotwal
  The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia.
• Hiddo J L Heerspink
  Department of Clinical Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands; The George Institute for Global Health, Sydney, Australia.
• Vlado Perkovic
  The George Institute for Global Health, University of New South Wales Sydney, Sydney, Australia.
• Robert A Fletcher
  Sensyne Health Plc, Schrodinger Building, Heatley Road, Oxford Science Park, Oxford, OX4 4GE, UK.
• Brendon L Neuen
  The George Institute for Global Health, University of New South Wales, Sydney, Australia.

Keywords

External Resources