The integration of big data analytics in healthcare has revolutionized patient care, disease management, and operational efficiency. This paper presents a Healthcare Data Analytics Platform (HDAP) that leverages artificial intelligence (AI), machine learning (ML), and cloud computing to analyze vast amounts of structured and unstructured healthcare data. The platform facilitates real-time data processing, predictive analytics, and decision support for healthcare providers, improving patient outcomes and resource allocation. Key components include electronic health record (EHR) integration, predictive modeling for disease outbreaks, and personalized treatment recommendations. The study also examines challenges such as data security, interoperability, and ethical considerations in healthcare analytics. Results demonstrate the platform’s potential to enhance clinical decision- making, reduce costs, and optimize healthcare delivery.
Healthcare Data Analytics, Artificial Intelligence, Machine Learning, Personalized Nutrition, Nutritional Recommendation System, Electronic Health Records (EHR), Predictive Analytics, Clinical Decision Support, Data Visualization, Power BI, Health Informatics, IoT in Healthcare, Dietary Assessment, Patient- Centered Care, Cloud Computing in Healthcare
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