Innovation in Healthcare through Technology and Artificial Intelligence – Case Study: VitalView Blood Pressure Monitoring System

Abstract

The rising prevalence of chronic diseases and the advancement of artificial intelligence and machine learning are driving significant shifts in the healthcare industry. Chronic diseases pose an urgent threat to the world’s healthcare systems due to the rising number of fatalities, making the demand for innovative approaches imperative. Applying VitalView, a blood pressure monitoring system, as a case study, this thesis explores the intersection of these fields. The system’s main goal is to employ AI and machine learning to offer personalized treatment for chronic diseases, especially blood pressure. To accomplish this, the study commences by examining the challenges faced by Albania’s healthcare system, in particular issues connected to access, costs, and service quality. The study then digs into the development of VitalView, an innovative solution that meets the needs of patients and healthcare professionals. The creation of an algorithm for data analysis and communication is at the core of this work. Autoregressive Integrated Moving Average (ARIMA), among other machine learning models, improves the platform’s ability to forecast blood pressure trends and simplify doctor-patient communication. The system also provides advice and recommendations for the patient’s general state of health. The case study methodology is employed with the objective of putting this system’s applications into action in real life situations. Its findings show the potential of AI and machine learning to boost communication, improve the management of chronic blood pressure diseases, and boost patient outcomes. This thesis demonstrates how innovative technologies could cope with pressing concerns of our time and contributes to the discussion on artificial intelligence in the healthcare industry. The VitalView system serves as an example of how innovation, data analysis, and user-centered design function together. It highlights how AI and machine learning have the potential to improve healthcare.