An Explainable Neural Oblivious Decision Ensemble Learning for Baldness Prediction Using Multidimensional Risk Factors

Background

Baldness is characterized by significant hair loss on the scalp and can be influenced by factors such as age, lifestyle, genetics, and personal habits. Explainable artificial intelligence methods can help address this issue by showing the factors that contribute to individual predictions. Therefore, this study proposes an Explainable Risk-Based Baldness Prediction model using Neural Oblivious Decision Ensembles (XRB-NODE). The proposed model is an ensemble-based framework for baldness prediction that incorporates multidimensional risk factors, including genetic, medical, lifestyle, nutritional, environmental, and demographic characteristics.