2019
DOI: 10.1111/exd.13958
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Machine learning for the prediction of sunscreen sun protection factor and protection grade of UVA

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 fa… Show more

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Cited by 3 publications
(2 citation statements)
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“…Most commonly, regression analysis has been used to develop equations for prediction (Apaolaza-Iba´n˜ez et al, 2011). Furthermore, machine learning, a computational analysis of the complex relationships between parameters that cannot easily be interpreted by the human mind, has been used for various purposes in the cosmetic and skincare research fields for regression analyses or development of prediction models (Cho et al, 2022;Shim et al, 2019). Given the multitude of parameters, encompassing both quantitative and qualitative data, our belief was that machine learning would be the most effective approach for developing RCS.…”
Section: Conceptual Framework and Hypothesesmentioning
confidence: 99%
“…Most commonly, regression analysis has been used to develop equations for prediction (Apaolaza-Iba´n˜ez et al, 2011). Furthermore, machine learning, a computational analysis of the complex relationships between parameters that cannot easily be interpreted by the human mind, has been used for various purposes in the cosmetic and skincare research fields for regression analyses or development of prediction models (Cho et al, 2022;Shim et al, 2019). Given the multitude of parameters, encompassing both quantitative and qualitative data, our belief was that machine learning would be the most effective approach for developing RCS.…”
Section: Conceptual Framework and Hypothesesmentioning
confidence: 99%
“…Thus, the Buscone et al 44 (2021) study challenges investigative dermatology to broaden its horizon from a long‐standing focus on ultraviolet light and its many facets in skin physiology, carcinogenesis, ageing and phototherapy 11,57–61 , 63–65 to the photobiomodulation of skin and its appendages in health and disease by visible light, 52 well beyond photodynamic therapy 65 and hair growth applications of blue light treatment 44,48 …”
mentioning
confidence: 99%