Predicting Hair Loss With AI: A Deep Learning Framework Combining Genetic And Scalp Health Data

This study presents a deep learning framework that predicts hair loss by integrating genetic, hormonal, scalp health, and lifestyle data. Convolutional Neural Networks (CNNs) are used to extract features from high-resolution scalp images, identifying thinning patterns and follicle health. Recurrent Neural Networks (RNNs), particularly Long Short-Term Memory (LSTM) networks, model temporal sequences of lifestyle and health data to capture longitudinal patterns in hair loss progression. This approach aims to enhance the understanding and prediction of hair loss by combining diverse data sources.