Automated Classification of Male and Female Pattern Hair Loss Stages Using EfficientNet According to the Hamilton-Norwood and Ludwig Scale

The study focuses on the automated classification of male and female pattern hair loss stages using the EfficientNet model, based on the Hamilton-Norwood and Ludwig scales. These scales are standard methods for assessing the severity of hair loss in men and women, respectively. The research aims to improve the accuracy and efficiency of diagnosing hair loss stages, which can aid in better treatment planning. The use of EfficientNet, a state-of-the-art convolutional neural network, suggests a promising advancement in dermatological diagnostics, potentially leading to more personalized and timely interventions for individuals experiencing alopecia.