AI-Based Healthcare Analytics for Predictive Modeling and Data Integration

Abstract

The rapidly increasing volume of healthcare data, including Electronic Health Records (EHR), medical imaging, and sensor data from wearables, presents significant opportunities to improve patient outcomes. This paper introduces an AI-powered healthcare analytics framework that integrates predictive modeling and multisource medical records, enabling early disease detection, personalized treatment, and proactive decision support. The framework leverages advanced machine learning techniques, including ensemble learning and deep learning, to derive actionable insights from both structured and unstructured big data. Key outcomes of the study demonstrate that incorporating clinical, genomic, and real-time sensor data enhances the accuracy and speed of diagnoses, resulting in improved prediction rates and reduced latency in patient care. This AI-assisted system has the potential to revolutionize healthcare delivery by supporting value-based care and personalized patient management.

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