Published in Scientific Papers. Series D. Animal Science, Vol. LXVII, Issue 2
Written by Maria-Luiza DULGHERU, Iuliana MARIN
Healthcare and life sciences represent a significant role in people’s lives, these two aspects governing their well-being and functioning. Redefining patient care methods and treatment solutions, working on thorough genomics studies and balancing healthcare costs have become an upfront priority for any healthcare and life science organization. A cloud infrastructure composed of applications, servers, networks, and data storage represents an effective solution to both business and technical goals, but also a modernization tool. For this study, we created a web-based program called HealthCloud, which facilitates medical data interoperability, provides automation services, and uses machine learning for predictions and insights related to the possibility of developing a cardiovascular disease, based on patient input regarding food and nutrition. Our results include a user-friendly interface, easy access to patient and doctor data, and a high accuracy of disease risk prediction with a machine learning model built in Amazon SageMaker. The proposed prototype proved its potential through the attained outcomes and presents an appropriate approach of healthcare management, which merges with cloud technology for the enhancement of care delivery.
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