Application of Naive Bayes Algorithm for Hair Loss Prediction

The study explores the application of the Naive Bayes algorithm to predict hair loss by analyzing personal data and clinical factors such as age, gender, stress levels, hormones, and family history. Early prediction of hair loss risk is crucial for more effective management. The research aims to enhance the accuracy of hair loss predictions, thereby potentially improving individual confidence and treatment outcomes.