The impact of machine learning on the prediction of diabetic foot ulcers - A systematic review.

Journal: Journal of tissue viability
Published Date:

Abstract

INTRODUCTION: Globally, diabetes mellitus poses a significant health challenge as well as the associated complications of diabetes, such as diabetic foot ulcers (DFUs). The early detection of DFUs is important in the healing process and machine learning may be able to help inform clinical staff during the treatment process.

Authors

  • Teagan Weatherall
    Skin Wounds and Trauma (SWaT) Research Centre, RCSI University of Medicine and Health Sciences, Dublin, Ireland; School of Nursing and Midwifery, RCSI University of Medicine and Health Sciences, Dublin, Ireland. Electronic address: teaganweatherall@rcsi.ie.
  • Pinar Avsar
    Skin Wounds and Trauma (SWaT) Research Centre, RCSI University of Medicine and Health Sciences, Dublin, Ireland; School of Nursing and Midwifery, RCSI University of Medicine and Health Sciences, Dublin, Ireland. Electronic address: pinaravsar@rcsi.ie.
  • Linda Nugent
    Skin Wounds and Trauma (SWaT) Research Centre, RCSI University of Medicine and Health Sciences, Dublin, Ireland; School of Nursing and Midwifery, RCSI University of Medicine and Health Sciences, Dublin, Ireland; Fakeeh College of Medical Sciences, Jeddah, Saudi Arabia. Electronic address: lindanugent@rcsi.ie.
  • Zena Moore
    Skin Wounds and Trauma (SWaT) Research Centre, RCSI University of Medicine and Health Sciences, Dublin, Ireland; School of Nursing and Midwifery, RCSI University of Medicine and Health Sciences, Dublin, Ireland; Fakeeh College of Medical Sciences, Jeddah, Saudi Arabia; School of Nursing and Midwifery, Griffith University, Southport, Queensland, Australia; Lida Institute, Shanghai, China; Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia; Department of Public Health, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium; University of Wales, Cardiff, UK; National Health and Medical Research Council Centre of Research Excellence in Wiser Wound Care, Menzies Health Institute Queensland, Southport, Queensland, Australia. Electronic address: zmoore@rcsi.ie.
  • John H McDermott
    Department of Endocrinology, Royal College of Surgeons in Ireland, Connolly Hospital Blanchardstown, Dublin, Ireland. Electronic address: johnmcdermott@rcsi.ie.
  • Seamus Sreenan
    Department of Endocrinology, Royal College of Surgeons in Ireland, Connolly Hospital Blanchardstown, Dublin, Ireland. Electronic address: ssreenan@rcsi.ie.
  • Hannah Wilson
    Skin Wounds and Trauma (SWaT) Research Centre, RCSI University of Medicine and Health Sciences, Dublin, Ireland; School of Nursing and Midwifery, RCSI University of Medicine and Health Sciences, Dublin, Ireland. Electronic address: wilsonhannah@rcsi.ie.
  • Natalie L McEvoy
    School of Nursing and Midwifery, RCSI University of Medicine and Health Sciences, Dublin, Ireland. Electronic address: natalielmcevoy@rcsi.ie.
  • Rosemarie Derwin
    School of Nursing and Midwifery, RCSI University of Medicine and Health Sciences, Dublin, Ireland. Electronic address: rosemariederwin@rcsi.ie.
  • Paul Chadwick
    Birmingham City University, Birmingham, UK; Spectral MD, London, UK. Electronic address: paul.chad@live.co.uk.
  • Declan Patton
    Skin Wounds and Trauma (SWaT) Research Centre, RCSI University of Medicine and Health Sciences, Dublin, Ireland; School of Nursing and Midwifery, RCSI University of Medicine and Health Sciences, Dublin, Ireland; Fakeeh College of Medical Sciences, Jeddah, Saudi Arabia; School of Nursing and Midwifery, Griffith University, Southport, Queensland, Australia; Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, New South Wales, Australia. Electronic address: declanpatton@rcsi.ie.