Artificial intelligence model substantially improves stratum corneum moisture content prediction from visible-light skin images and skin feature factors.

Journal: Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
PMID: 37632180

Abstract

BACKGROUND: Appropriate skin treatment and care warrants an accurate prediction of skin moisture. However, current diagnostic tools are costly and time-consuming. Stratum corneum moisture content has been measured with moisture content meters or from a near-infrared image.

Authors

  • Tomoyuki Shishido
    Department of Information and Communications Engineering,Biomedical AI Research Unit, Tokyo Institute of Technology, Tokyo, Japan.
  • Yasuhiro Ono
    Enspirea, LLC, Chicago, Illinois, USA.
  • Itsuo Kumazawa
    Laboratory for Future, Interdisciplinary Research of Science and Technology, Institute of Innovative Research, Tokyo Institute of Technology, Tokyo, Japan.
  • Ichiro Iwai
    Saticine Medical, Research Institute, Tokyo, Japan.
  • Kenji Suzuki
    Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan.

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