Hair Analysis Based on Medical History and Spatial-Temporal Data

    January 2026 in “ Periodicals of Engineering and Natural Sciences (International University of Sarajevo) ”
    Ahmed Mahdi Abdulkadium, Raid Abd Alreda Shekan, Ali Abdulbaqi Abdulazeez
    TLDR Machine learning can predict hair health accurately using personal data.
    The paper explores the use of machine learning, specifically SVM and J48 algorithms, to analyze medical data for determining hair health. By incorporating spatial-temporal images along with factors like gender, age, and hairstyle, the study aims to predict hair health. The research tested 1,066 samples using cross-validation, achieving an 87.14% correct classification rate and a real-time performance of 89.5%. The study demonstrates the compatibility between hairstyle and age-gender factors in predicting hair health.
    Discuss this study in the Community →