AI Driven Integrated Management of Diabetes Mellitus And Hypertension

Abstract

Diabetes Mellitus and Hypertension are two of the most common chronic illnesses in the world, and when they strike at once, they are probably going to be very difficult and vulnerable to high risks of developing cardiovascular issues, in case of unsuccessful treatment. The conventional medical systems are based on the following principles: making a reservation for check-ups, handling documents, and may result in interventions, follow-ups, and treatment outcomes. In this paper, an AIbased Integrated Management System, which helps to provide continuous, personalized, and dynamic care to Diabetes Mellitus and Hypertension patients, is presented. The system includes health data of the wearable devices and patients’ data in realtime and automated analysis of the data with the help of machine learning models that predict glucose, identify the trend of blood pressure, identify possible risks, and detect abnormalities. The smart decision support system is then developed, which gives recommendations to individuals on medication compliance, lifestyle modification, nutrition plan, and statements on significant deviations. Patient dashboards and clinician monitoring applications with predictive analytics to enable timely medical interventions can also be accessed on the platform. The proposed system will be more effective in managing the disease, relieving the doctor’s workload, and providing patients with operating information on how to maintain healthy conditions with the power of AI-driven analytics and focus on multimodal health indicators. As mentioned in this work, the proposed system is scalable and can lead to the betterment of the outcomes of chronic diseases through continuous monitoring, disease identification at the early stage, and personalized care based on data.