Sakhi - Predictive Modeling for Early Detection of Women’s Health Conditions using Machine Learning
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Abstract
For those who are designated as female at birth, health is essential to general well-being; nevertheless, conditions such as PCOS, endometriosis, and UTIs pose serious obstacles to reproductive health. Sakhi is a unique application that uses machine learning (ML) techniques to detect disorders proactively and solve them. Sakhi uses a customized questionnaire to gather user data. Machine learning methods such as Decision Tree Classifier, Logistic Regression, Random Forest Classifier, Support Vector Machines, and XGBoost classifier are then used to analyze trends in the user’s health history and symptoms. Sakhi is a non-invasive platform for users to monitor and manage their health health, offering individualized insights and suggestions, by spotting deviations from typical swings in hormone levels. This creative strategy encourages access to healthcare services and understanding of health, enabling people to mitigate the effects of health disorders through proactive healthcare management.