BaldPredict: AI-Driven Prediction Model for Alopecia Areata

The study "BaldPredict: AI-Driven Prediction Model for Alopecia Areata" explores the use of machine learning (ML) to improve the diagnosis of alopecia areata (AA), an autoimmune disease causing patchy hair loss. Traditional diagnostic methods rely heavily on visual inspection, which often lacks accuracy. The research utilizes a dataset of 1,000 images of healthy hair and over 500 images of AA-affected hair, enhanced through preprocessing techniques. Various classifiers, including random forest, support vector machines (SVM), k-nearest network (KNN), and convolutional neural networks (CNN), were tested, achieving accuracy rates of 89%, 90%, 83%, and 91.9%, respectively. The study demonstrates that ML-based classification algorithms can significantly enhance the identification and diagnosis of AA, offering a more precise and reliable alternative to traditional methods.