Machine Learning Decision Support Systems for Health Risk Assessment examines machine learning methods and decision support concepts for assessing health risks. The book explores healthcare data, predictive modeling, classification, risk estimation, and data-driven decision support. It presents a technical perspective on how computational models can assist interpretation of health-related information and support structured risk assessment. Topics include machine learning, health risk prediction, clinical decision support, healthcare analytics, predictive analytics, data analysis, model-based assessment, and intelligent decision systems. The discussion connects artificial intelligence, machine learning, healthcare informatics, and risk assessment. Designed for students, researchers, engineers, and data professionals, this volume provides a concise foundation for understanding computational approaches to health risk assessment and decision-oriented healthcare applications. It provides context for further study of healthcare data and predictive systems in healthcare.
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