Artificial intelligence-based prescription of personalized scalp cosmetics improved the scalp condition: efficacy results from 100 participants

AbstractBackground: Scalp-related symptoms such as dandruff and itching are common with diverse underlying etiologies. We previously proposed a novel classification and scoring system for scalp conditions, called the scalp photographic index (SPI); it grades five scalp features using trichoscopic im...

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Main Authors: Bo Ri Kim (Author), Min Jae Kim (Author), Jieun Koo (Author), Hwa-Jung Choi (Author), Kyung Ho Paik (Author), Soon Hyo Kwon (Author), Hye-Ryung Choi (Author), Chang Hun Huh (Author), Jung Won Shin (Author), Dong-sun Park (Author), Jung-Im Na (Author)
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Published: Taylor & Francis Group, 2024-12-01T00:00:00Z.
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042 |a dc 
100 1 0 |a Bo Ri Kim  |e author 
700 1 0 |a Min Jae Kim  |e author 
700 1 0 |a Jieun Koo  |e author 
700 1 0 |a Hwa-Jung Choi  |e author 
700 1 0 |a Kyung Ho Paik  |e author 
700 1 0 |a Soon Hyo Kwon  |e author 
700 1 0 |a Hye-Ryung Choi  |e author 
700 1 0 |a Chang Hun Huh  |e author 
700 1 0 |a Jung Won Shin  |e author 
700 1 0 |a Dong-sun Park  |e author 
700 1 0 |a Jung-Im Na  |e author 
245 0 0 |a Artificial intelligence-based prescription of personalized scalp cosmetics improved the scalp condition: efficacy results from 100 participants 
260 |b Taylor & Francis Group,   |c 2024-12-01T00:00:00Z. 
500 |a 10.1080/09546634.2024.2337908 
500 |a 1471-1753 
500 |a 0954-6634 
520 |a AbstractBackground: Scalp-related symptoms such as dandruff and itching are common with diverse underlying etiologies. We previously proposed a novel classification and scoring system for scalp conditions, called the scalp photographic index (SPI); it grades five scalp features using trichoscopic images with good reliability. However, it requires trained evaluators.Aim: To develop artificial intelligence (AI) algorithms for assessment of scalp conditions and to assess the feasibility of AI-based recommendations on personalized scalp cosmetics.Methods: Using EfficientNet, convolutional neural network (CNN) models (SPI-AI) ofeach scalp feature were established. 101,027 magnified scalp images graded according to the SPI scoring were used for training, validation, and testing the model Adults with scalp discomfort were prescribed shampoos and scalp serums personalized according to their SPI-AI-defined scalp types. Using the SPI, the scalp conditions were evaluated at baseline and at weeks 4, 8, and 12 of treatment.Results: The accuracies of the SPI-AI for dryness, oiliness, erythema, folliculitis, and dandruff were 91.3%, 90.5%, 89.6%, 87.3%, and 95.2%, respectively. Overall, 100 individuals completed the 4-week study; 43 of these participated in an extension study until week 12. The total SPI score decreased from 32.70 ± 7.40 at baseline to 15.97 ± 4.68 at week 4 (p < 0.001). The efficacy was maintained throughout 12 weeks.Conclusions: SPI-AI accurately assessed the scalp condition. AI-based prescription of tailored scalp cosmetics could significantly improve scalp health. 
546 |a EN 
690 |a Artificial intelligence 
690 |a dandruff 
690 |a evaluation 
690 |a folliculitis 
690 |a prescription 
690 |a scalp 
690 |a Dermatology 
690 |a RL1-803 
655 7 |a article  |2 local 
786 0 |n Journal of Dermatological Treatment, Vol 35, Iss 1 (2024) 
787 0 |n https://www.tandfonline.com/doi/10.1080/09546634.2024.2337908 
787 0 |n https://doaj.org/toc/0954-6634 
787 0 |n https://doaj.org/toc/1471-1753 
856 4 1 |u https://doaj.org/article/a5ccab92e912401a99c6561bd3d8c7dd  |z Connect to this object online.