Exploring AI and IoT Integration for Medicine Recommendation with Chimp Optimized Dynamic XGBoost (CO-DXB)

An Internet of Things (IoT) enabled medicine recommendation system for heart disease patients relies on remote monitoring of key health metrics like blood pressure and cholesterol levels. Machine learning algorithms can evaluate real-time data from heart disease patients to prescribe individualized drug regimens using IoT-enabled healthcare technologies. These algorithms ensure accurate and flexible treatment regimens by taking lifestyle characteristics, vital signs and past medical records. In this paper, we proposed chimp optimized dynamic XGBoost (CO-DXB) for recommend medicines for heart patients. We gathered 76 raw factors in the heart disease dataset. We evaluate the performance of our proposed method based on metrics such as accuracy (94%), recall (89%), precision (92%) and F1-score (90%) are compared to the existing method. Our proposed approach demonstrates superior performance in recommending medication for patients compared to existing methods.