This paper introduces a novel deep learning-based predictive analytics framework aimed at transforming personalized healthcare. By leveraging diverse data sources, including electronic health records (EHRs) and genomic information, the proposed approach predicts patient outcomes with enhanced precision and provides tailored treatment recommendations. The framework’s performance was evaluated on a large-scale EHR dataset, showcasing significant improvements in predictive accuracy and efficiency over traditional machine learning methods. Key findings emphasize the transformative potential of deep learning in delivering proactive, personalized healthcare solutions, ultimately contributing to better patient outcomes and optimized healthcare delivery systems.
Deep Learning, Predictive Analytics, Personalized Healthcare, Electronic Health Records (EHRs), Genomic Data
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