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Artificial intelligence model substantially improves stratum corneum moisture content prediction from visible-light skin images and skin feature factors.
Shishido, Tomoyuki; Ono, Yasuhiro; Kumazawa, Itsuo; Iwai, Ichiro; Suzuki, Kenji.
Affiliation
  • Shishido T; Department of Information and Communications Engineering,Biomedical AI Research Unit, Tokyo Institute of Technology, Tokyo, Japan.
  • Ono Y; Shishido & Associates, Tokyo, Japan.
  • Kumazawa I; Enspirea, LLC, Chicago, Illinois, USA.
  • Iwai I; Department of Information and Communications Engineering, Laboratory for Future Interdisciplinary Research of Science and Technology, Tokyo Institute of Technology, Tokyo, Japan.
  • Suzuki K; Saticine Medical, Research Institute, Tokyo, Japan.
Skin Res Technol ; 29(8): e13414, 2023 Aug.
Article in En | MEDLINE | ID: mdl-37632180
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Skin / Artificial Intelligence Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Skin Res Technol Journal subject: DERMATOLOGIA Year: 2023 Document type: Article Affiliation country: Japan Country of publication: United kingdom
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Skin / Artificial Intelligence Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Skin Res Technol Journal subject: DERMATOLOGIA Year: 2023 Document type: Article Affiliation country: Japan Country of publication: United kingdom