International Journal of Science, Engineering and TechnologyAuthors: Pujala Sivaleela, M.Prasanna Kumar
Abstract: Today, because to advancements in both technology and healthcare, people may have access to affordable, personalised health assistance right where they are. This research presents a method that may help individuals with their health by giving them detailed information on their health and being able to forecast when they may become sick. In order to foretell potential health problems, users are asked to provide three main symptoms together with basic biographical details such as gender and age. Decision trees, random forests, naive bayes, logistic regression, support vector machines (SVMs), K-nearest neighbours, and XGBoost are the seven machine learning models that the system uses to provide a final prediction using a voting ensemble model. In order to provide thorough descriptions of the expected illness, including its origins, symptoms, potential treatments, and remedies, the system integrates generative AI with predictive analytics. The generative AI model takes into account the user's age and gender to provide information that is personalised to their requirements. The reliability and effectiveness of the system may be shown by evaluation metrics including F1-score, accuracy, precision, and recall. People are better able to make informed choices about their health because to our user-friendly platform that makes health information freely accessible.
DOI: http://doi.org/10.5281/zenodo.20280806
