TLDR The AI model accurately classifies Alopecia Areata with 96.94% accuracy.
The study introduces the AB-MTEDeep network, an AI model combining Faster Residual Convolutional Neural Network and Long Short-Term Memory network, for classifying Alopecia Areata (AA) in scalp images. It utilizes a novel data augmentation model, AA-Generative Adversarial Network (AA-GAN), to generate a large number of high-quality synthetic images that closely resemble real images. These images are used to train the AB-MTEDeep model, resulting in a classification accuracy of 96.94% for AA.
47 citations
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December 2020 in “Journal of the European Academy of Dermatology and Venereology” The document concludes that understanding and treating hair loss requires recognizing its various types and using appropriate diagnostic tools and treatments.
53 citations
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February 2020 in “Expert Opinion on Pharmacotherapy” Finasteride and minoxidil work best together for hair loss.
74 citations
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January 2020 in “IEEE Access” ScalpEye accurately diagnoses scalp issues like dandruff and hair loss.
May 2023 in “Indian journal of science and technology” The new deep learning system can accurately recognize hair loss conditions with a 95.11% success rate.
Machine learning can accurately predict hair loss early, improving treatment options.
185 citations
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August 2005 in “Autoimmunity Reviews” Alopecia areata is an autoimmune condition causing hair loss due to the immune system attacking hair follicles, often influenced by genetics and stress.
148 citations
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December 2018 in “Journal of autoimmunity” Alopecia areata is an autoimmune disease causing patchy hair loss, often with other autoimmune disorders, but its exact causes are unknown.
15 citations
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January 2023 in “Antioxidants” Oxidative stress plays a significant role in alopecia areata, and new treatments may include JAK inhibitors and antioxidants.
