Classification Framework for Healthy Hair and Alopecia Areata: A Machine Learning Approach

The document "Classification Framework for Healthy Hairs and Alopecia Areata: A Machine Learning (ML) Approach" presents a study that used machine learning to differentiate between healthy hair and hair affected by Alopecia Areata. The researchers developed a classification framework using a dataset of 1000 images, 500 of healthy hair and 500 of hair with Alopecia Areata. The machine learning model achieved an accuracy of 92.3% in identifying Alopecia Areata. The study concludes that machine learning can be a valuable tool in the field of trichology for early detection and treatment of hair loss conditions like Alopecia Areata.