A machine learning approach for the identification of new biomarkers for knee osteoarthritis development in overweight and obese women.

Journal: Osteoarthritis and cartilage
PMID: 28899843

Abstract

OBJECTIVE: Knee osteoarthritis (OA) is among the higher contributors to global disability. Despite its high prevalence, currently, there is no cure for this disease. Furthermore, the available diagnostic approaches have large precision errors and low sensitivity. Therefore, there is a need for new biomarkers to correctly identify early knee OA.

Authors

  • N Lazzarini
    ICOS Research Group, School of Computing, Newcastle University, UK; D-BOARD Consortium, An FP7 Programme By the European Committee.
  • J Runhaar
    D-BOARD Consortium, An FP7 Programme By the European Committee; Erasmus University Medical Center Rotterdam, the Netherlands, Dept. of General Practice.
  • A C Bay-Jensen
    D-BOARD Consortium, An FP7 Programme By the European Committee; Nordic Bioscience, Copenhagen, Denmark.
  • C S Thudium
    D-BOARD Consortium, An FP7 Programme By the European Committee; Nordic Bioscience, Copenhagen, Denmark.
  • S M A Bierma-Zeinstra
    D-BOARD Consortium, An FP7 Programme By the European Committee; Erasmus University Medical Center Rotterdam, the Netherlands, Dept. of General Practice; Erasmus University Medical Center Rotterdam, the Netherlands, Dept. of Orthopedics.
  • Y Henrotin
    D-BOARD Consortium, An FP7 Programme By the European Committee; University of Liège, Belgium; Artialis SA, Liège, Belgium.
  • J Bacardit
    ICOS Research Group, School of Computing, Newcastle University, UK; D-BOARD Consortium, An FP7 Programme By the European Committee. Electronic address: jaume.bacardit@newcastle.ac.uk.

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