Artificial intelligence-based prescription of personalized scalp cosmetics improved the scalp condition: efficacy results from 100 participants
Background: 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 wit...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | Journal of Dermatological Treatment |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/09546634.2024.2337908 |
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| author | Bo Ri Kim Min Jae Kim Jieun Koo Hwa-Jung Choi Kyung Ho Paik Soon Hyo Kwon Hye-Ryung Choi Chang Hun Huh Jung Won Shin Dong-sun Park Jung-Im Na |
| author_facet | Bo Ri Kim Min Jae Kim Jieun Koo Hwa-Jung Choi Kyung Ho Paik Soon Hyo Kwon Hye-Ryung Choi Chang Hun Huh Jung Won Shin Dong-sun Park Jung-Im Na |
| author_sort | Bo Ri Kim |
| collection | DOAJ |
| description | Background: 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. |
| format | Article |
| id | doaj-art-a5ccab92e912401a99c6561bd3d8c7dd |
| institution | DOAJ |
| issn | 0954-6634 1471-1753 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Journal of Dermatological Treatment |
| spelling | doaj-art-a5ccab92e912401a99c6561bd3d8c7dd2025-08-20T02:49:32ZengTaylor & Francis GroupJournal of Dermatological Treatment0954-66341471-17532024-12-0135110.1080/09546634.2024.2337908Artificial intelligence-based prescription of personalized scalp cosmetics improved the scalp condition: efficacy results from 100 participantsBo Ri Kim0Min Jae Kim1Jieun Koo2Hwa-Jung Choi3Kyung Ho Paik4Soon Hyo Kwon5Hye-Ryung Choi6Chang Hun Huh7Jung Won Shin8Dong-sun Park9Jung-Im Na10Department of Dermatology, Seoul National University Bundang Hospital, Seongnam, KoreaDepartment of Dermatology, Seoul National University Bundang Hospital, Seongnam, KoreaAram Huvis Co., Ltd, Seongnam, KoreaDepartment of Beauty Art, Youngsan University, Busan, South KoreaDepartment of Dermatology, Seoul National University Bundang Hospital, Seongnam, KoreaDepartment of Dermatology, Kyung Hee University Hospital at Gangdong, Seoul, KoreaDepartment of Dermatology, Seoul National University Bundang Hospital, Seongnam, KoreaDepartment of Dermatology, Seoul National University Bundang Hospital, Seongnam, KoreaDepartment of Dermatology, Seoul National University Bundang Hospital, Seongnam, KoreaAram Huvis Co., Ltd, Seongnam, KoreaDepartment of Dermatology, Seoul National University Bundang Hospital, Seongnam, KoreaBackground: 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.https://www.tandfonline.com/doi/10.1080/09546634.2024.2337908Artificial intelligencedandruffevaluationfolliculitisprescriptionscalp |
| spellingShingle | Bo Ri Kim Min Jae Kim Jieun Koo Hwa-Jung Choi Kyung Ho Paik Soon Hyo Kwon Hye-Ryung Choi Chang Hun Huh Jung Won Shin Dong-sun Park Jung-Im Na Artificial intelligence-based prescription of personalized scalp cosmetics improved the scalp condition: efficacy results from 100 participants Journal of Dermatological Treatment Artificial intelligence dandruff evaluation folliculitis prescription scalp |
| title | Artificial intelligence-based prescription of personalized scalp cosmetics improved the scalp condition: efficacy results from 100 participants |
| title_full | Artificial intelligence-based prescription of personalized scalp cosmetics improved the scalp condition: efficacy results from 100 participants |
| title_fullStr | Artificial intelligence-based prescription of personalized scalp cosmetics improved the scalp condition: efficacy results from 100 participants |
| title_full_unstemmed | Artificial intelligence-based prescription of personalized scalp cosmetics improved the scalp condition: efficacy results from 100 participants |
| title_short | Artificial intelligence-based prescription of personalized scalp cosmetics improved the scalp condition: efficacy results from 100 participants |
| title_sort | artificial intelligence based prescription of personalized scalp cosmetics improved the scalp condition efficacy results from 100 participants |
| topic | Artificial intelligence dandruff evaluation folliculitis prescription scalp |
| url | https://www.tandfonline.com/doi/10.1080/09546634.2024.2337908 |
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