ML Model For Detection of Depression in Menopause Women

Menopause, an inevitable milestone in a woman’s journey, signifies not only the onset of physical transformations but also the potential emergence of mental health complexities. This study investigates the potential of machine learning to predict depression in menopausal women, aiming to improve their well-being. Depression is a prevalent concern during menopause, yet limited specialist access and knowledge gaps hinder effective intervention. We have developed a supervised multi-classifier machine learning system to predict depression and its severity, evaluating various classification algorithms. Our findings demonstrate high accuracy (97%) using a Random Forest model, suggesting promise as an AI-powered tool in this domain.