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Enhancing Predictive Analytics for Healthcare: Addressing Limitations and Proposing Advanced Solutions
MITA, Rutgers University, Newark, NJ, USA
- 1 MITA, Rutgers University, Newark, NJ, USA
Journal of Intelligent Learning Systems and Applications·Volume 17 (2024)·Pages 36–43·Published 26 December 2024·DOI10.4236/jilsa.2025.171004
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Abstract
The paper reviews some of the major issues that occur in the application of big data analytics and predictive modeling in health, as obtained from the original study. It highlights challenges related to data integration, quality, model interpretability, and clinical relevance. It suggests improvements in terms of hybrid machine learning models, enhanced methods for data preprocessing, and considerations on ethics. In such a way, it is trying to provide a roadmap for future research and practical implementation of predictive analytics in healthcare.
KeywordsBig Data AnalyticsPredictive AnalyticsHealthcareClinical Decision-MakingData QualityPrivacyHybrid ModelsMachine Learning
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