Visual classification of pressure injury stages for nurses: A deep learning model applying modern convolutional neural networks.

Abstract

Authors

• Suryang Seo
  Department of Nursing, SMG-SNU Boramae Medical Center, Seoul National University College of Medicine, Seoul, Republic of Korea.
• Jaeyeon Kang
  Department of Nursing, SMG-SNU Boramae Medical Center, Seoul National University College of Medicine, Seoul, Republic of Korea.
• In Hyang Eom
  Department of Nursing, SMG-SNU Boramae Medical Center, Seoul National University College of Medicine, Seoul, Republic of Korea.
• Hyeji Song
  Department of Nursing, SMG-SNU Boramae Medical Center, Seoul National University College of Medicine, Seoul, Republic of Korea.
• Jun Ho Park
  Department of Plastic and Reconstructive Surgery, SMG-SNU Boramae Medical Center, Seoul National University College of Medicine, Seoul, Republic of Korea.
• Youngsoo Lee
  From the Department of Radiology and Research Institute of Radiology (J.C., H.J.H., J.B.S., S.M.L., K.J., R.P., J.K., N.K.), Department of Convergence Medicine, Biomedical Engineering Research Center (J. Yun), and Department of Clinical Epidemiology and Biostatistics (M.J.K.), University of Ulsan College of Medicine, Asan Medical Center, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul 138-735, Korea; Department of Radiology, Soonchunhyang University Seoul Hospital, Soonchunhyang University College of Medicine, Seoul, Korea (J.J.); Department of Internal Medicine, Ajou University School of Medicine, Suwon, Korea (Y.L.); Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea (H.J.); and Coreline Soft, Seoul, Korea (J. Yi, D.Y., B.K.).
• Haeyoung Lee
  Red Cross College of Nursing, Chung-Ang University, Seoul, Republic of Korea.

Keywords

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