Transforming Healthcare with MedInsight: A Guide to Intelligent Decision Support

A novel Prediction System has been developed to address the lack of a unified approach for multi-disease prediction in healthcare machine learning models. The To detect various ailments, the system uses machine learning neural network as well as artificial intelligence. simultaneously, specifically targeting heart, liver, and diabetes conditions. The system uses Support Vector Machine and logistic regression models to analyze heart disorders, diabetes, and breast cancer. The logistic regression model, trained on 8,000 patients, achieved an impressive overall accuracy of 85%. It was particularly effective in predicting hypertension and hyperlipidaemia, with accuracies of 90% and 87%, respectively. The system also showed proficiency in predicting diabetes and heart disease, with accuracies of 82% and 78%. This research represents a promising step towards a more comprehensive and accurate multi-disease prediction system.