74 citations
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January 2020 in “IEEE Access” This study reports that the ScalpEye system accurately diagnosed dandruff, folliculitis, hair loss, and oily hair with a precision range of 97.41% to 99.09%.
February 2024 in “Frontiers in physics” This study developed a model for detecting sparse hair clusters using enhanced object detection neural networks and medical images, which accurately identifies and counts sparse hair clusters with greater accuracy and efficiency than existing methods.
January 2026 in “Open Science Framework” This scoping review describes the current use of artificial intelligence in alopecia research, highlighting AI's evolution from diagnostic to prognostic applications in dermatology and identifying gaps in multimodal integration and fairness across demographics.
50 citations
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December 2011 in “Skin Research and Technology” In this study, the researchers reported that their novel algorithm for hair restoration in dermoscopy images achieved high accuracy and texture preservation, outperforming other techniques in diagnostic accuracy and texture quality measures.
August 2024 in “Journal of the National Medical Association” ChatGPT is more accurate at diagnosing hair disorders in lighter skin tones than darker ones.
