TLDR AI can accurately diagnose hair and scalp conditions and suggest treatments.
This study developed a deep learning model based on the VGG architecture to predict hair disorders and provide tailored therapeutic suggestions. By using a convolutional neural network (CNN) and transfer learning, the model was trained on a diverse set of images to accurately recognize hair and scalp conditions such as dandruff, fungal infections, and alopecia. The AI-based system demonstrated high sensitivity and specificity, reducing false-positive and false-negative outcomes, and has the potential to transform dermatology by offering prompt and accurate diagnoses and customized treatment recommendations. This research highlights the role of artificial intelligence in enhancing healthcare outcomes in dermatology and skincare.
8 citations
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August 2021 in “Computational and Mathematical Methods in Medicine” Machine learning can accurately identify Alopecia Areata, aiding in early detection and treatment of this hair loss condition.
November 2020 in “DOAJ (DOAJ: Directory of Open Access Journals)” Inflammation plays a key role in male and female pattern hair loss, and focusing on this could help develop better treatments.
GFC injections significantly improved hair growth and quality with minimal side effects.
1 citations
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August 2022 in “JAAD case reports” Tofacitinib and oral minoxidil may help treat Sisaipho alopecia areata.
7 citations
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January 2021 in “Journal of Cosmetics Dermatological Sciences and Applications” Improving the scalp's barrier function can help reduce dandruff and maintain scalp health.
3 citations
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August 2020 in “Journal of cosmetic dermatology” The scalp care solution with Timosaponin B-II improved scalp hydration, reduced dandruff, and helped prevent hair loss.
January 2017 in “Journal of Cosmetics, Dermatological Sciences and Applications” Chinese women's hair gets thinner and grayer with age, and scalp conditions change, especially after 40.
