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Machine learning for the prediction of sunscreen sun protection factor and protection grade of UVA.
Shim, Jiyong; Lim, Jun Man; Park, Sun Gyoo.
  • Shim J; Cosmetic R&D Center, LG Household & Healthcare Ltd, Seoul, Korea.
  • Lim JM; Cosmetic R&D Center, LG Household & Healthcare Ltd, Seoul, Korea.
  • Park SG; Cosmetic R&D Center, LG Household & Healthcare Ltd, Seoul, Korea.
Exp Dermatol ; 28(7): 872-874, 2019 07.
Article en En | MEDLINE | ID: mdl-31077472
ABSTRACT
We report a prediction model for sunscreen sun protection factor (SPF) and protection grade of ultraviolet (UV) A (PA) based on machine learning. We illustrate with real clinical test results of UV protection ability of sunscreen for SPF and PA. With approximately 2200 individual clinical results for both SPF and PA level detection, individually, we were able to see that active ingredient information can provide accurate SPF and PA prediction rates through machine learning. Furthermore, we included four new factors-presence of pigment, concentration of pigment grade titanium dioxide, type of formulation and type of product-as additional information for the prediction model and were able to see increased prediction rates as results.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Piel / Protectores Solares / Rayos Ultravioleta / Aprendizaje Automático Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Año: 2019 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Piel / Protectores Solares / Rayos Ultravioleta / Aprendizaje Automático Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Año: 2019 Tipo del documento: Article