74 citations
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January 2020 in “IEEE Access” ScalpEye accurately diagnoses scalp issues like dandruff and hair loss.
February 2024 in “Frontiers in physics” The new model detects hair clusters more accurately and efficiently, helping with early hair loss treatment and diagnosis.
January 2026 in “Open Science Framework” This scoping review systematically maps the use of AI and ML in alopecia research, highlighting the evolution from diagnostic tools to more advanced prognostic frameworks. It identifies the dominance of CNNs for image-based diagnosis, limited multimodal integration, and a lack of prognostic or causal modeling. Key gaps include the need for generative prognosis frameworks, fairness evaluations, privacy-aware systems, and treatment-response prediction. The review provides a taxonomy of AI approaches, visual aids, and recommendations for future research, emphasizing the development of equitable AI tools for personalized prognosis and treatment planning in alopecia care.
50 citations
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December 2011 in “Skin Research and Technology” The algorithm effectively removes hair from skin images, improving melanoma diagnosis accuracy.
August 2024 in “Journal of the National Medical Association” ChatGPT is more accurate at diagnosing hair disorders in lighter skin tones than darker ones.