INTRODUCTION
Hair loss is a prevalent health condition affecting up to 50% of women and 80% of men during their lifetime.1 Many refrain from professional dermatological consultations and procedures due to their high cost and long appointment wait time, turning instead to generic one-size-fits-all solutions that can be irritating and ineffective. Hair loss treatment is a long process; therefore, ease of use is essential for treatment compliance.2 Combining accessible skin or hair assessment and a large arsenal of topical and oral nutraceuticals personalized to the individual's needs can further improve the benefits of non-medicated hair growth research and offer a more affordable and easily accessible alternative or addition to current medicated alternatives. A retrospective cohort study found better outcomes from combination therapy (topical minoxidil and oral nutraceutical) than topical minoxidil alone to treat chemotherapy-induced alopecia.3 Combination therapy induced higher improvement in hair density and thickness compared to monotherapy with minoxidil.
Advancements in smartphone camera technology, computer vision, and deep learning artificial intelligence (AI) have facilitated the development of AI-driven platforms that offer personalized dermatological assessments via personal devices, thereby democratizing access to specialized care. Skin and hair conditions, due to their visual nature, are particularly amenable to AI exploration.4,5 Moreover, increasing evidence supports the benefits of nutraceuticals for individuals with hair loss. While previous research has primarily focused on the impact of single topical or oral products, this study aims to employ AI-driven assessments to curate a personalized set of topical and oral products targeting multiple mechanisms of hair loss to maximize efficacy. In a pilot study,6 data from 30 women with androgenetic alopecia demonstrated that AI-based assessments aligned with human dermatologist evaluations in 28 out of 30 cases, resulting in a 94% accuracy rate. This current study investigates the potential of a proprietary AI platform developed by MDalgorithms, Inc.7 to deliver customized over-the-counter sets of topical and oral products tailored to individual needs and characteristics.
The AI model tested in this study was trained on tens of thousands of scalp images to evaluate hair loss pattern and severity, providing grading and visual heatmap of hair loss. This assessment allows the AI to customize a treatment plan for each individual, which includes a personalized set of topical serums, shampoos, and oral supplements.
Advancements in smartphone camera technology, computer vision, and deep learning artificial intelligence (AI) have facilitated the development of AI-driven platforms that offer personalized dermatological assessments via personal devices, thereby democratizing access to specialized care. Skin and hair conditions, due to their visual nature, are particularly amenable to AI exploration.4,5 Moreover, increasing evidence supports the benefits of nutraceuticals for individuals with hair loss. While previous research has primarily focused on the impact of single topical or oral products, this study aims to employ AI-driven assessments to curate a personalized set of topical and oral products targeting multiple mechanisms of hair loss to maximize efficacy. In a pilot study,6 data from 30 women with androgenetic alopecia demonstrated that AI-based assessments aligned with human dermatologist evaluations in 28 out of 30 cases, resulting in a 94% accuracy rate. This current study investigates the potential of a proprietary AI platform developed by MDalgorithms, Inc.7 to deliver customized over-the-counter sets of topical and oral products tailored to individual needs and characteristics.
The AI model tested in this study was trained on tens of thousands of scalp images to evaluate hair loss pattern and severity, providing grading and visual heatmap of hair loss. This assessment allows the AI to customize a treatment plan for each individual, which includes a personalized set of topical serums, shampoos, and oral supplements.
PATIENTS AND METHODS
This study employed a prospective single-center, single-blind clinical trial design to assess the effectiveness of an AI-based personalized hair loss treatment. Thirty-eight women aged 34 to 65 with self-reported hair thinning were recruited for the trial. The study consisted of three clinic visits at baseline, week 12, and week 24, along with two self-assessment evaluations at week 4 and week 8.
