Synergizing Data Envelopment Analysis And Machine Learning For Performance Optimization In Healthcare
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Synergizing Data Envelopment Analysis and Machine Learning for Performance Optimization in Healthcare
Healthcare systems face the challenge of delivering high-quality care while efficiently managing costs and resources. Traditional methods of performance evaluation often fall short when addressing the complex and diverse nature of healthcare operations. Data envelopment analysis (DEA) has been used to measure the efficiency of healthcare providers, but its linear, deterministic nature limits its adaptability to dynamic environments. In contrast, machine learning (ML) can handle complex, non-linear relationships and high-dimensional data, offering deeper insights and predictive capabilities. The synergy between DEA and ML presents an opportunity to overcome these limitations and drive more effective performance optimization. It leads to efficiency assessments through predictive analytics and improved resource allocation with data-driven insights and optimizing clinical pathways and decision support systems for better patient outcomes. Synergizing Data Envelopment Analysis and Machine Learning for Performance Optimization in Healthcare explores the integration of DEA and ML to enhance performance optimization in healthcare, improving efficiency, care quality, and resource management. It examines theoretical foundations, methodological innovations, and practical applications, providing a comprehensive resource with a key focus on development of algorithms to address challenges in healthcare optimization. Covering topics such as healthcare equipment manufacturing, human augmentation, and robotic surgery, this book is an excellent resource for hospital administrators, clinical managers, clinical decision-makers, policymakers, public health officials, professionals, researchers, scholars, academics, and more.
Predictive Intelligence in Biomedical and Health Informatics
Author: Rajshree Srivastava
language: en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date: 2020-10-12
Predictive Intelligence in Biomedical and Health Informatics focuses on imaging, computer-aided diagnosis and therapy as well as intelligent biomedical image processing and analysis. It develops computational models, methods and tools for biomedical engineering related to computer-aided diagnostics (CAD), computer-aided surgery (CAS), computational anatomy and bioinformatics. Large volumes of complex data are often a key feature of biomedical and engineering problems and computational intelligence helps to address such problems. Practical and validated solutions to hard biomedical and engineering problems can be developed by the applications of neural networks, support vector machines, reservoir computing, evolutionary optimization, biosignal processing, pattern recognition methods and other techniques to address complex problems of the real world.
Human Autonomy in Cross-Cultural Context
Author: Valery I. Chirkov
language: en
Publisher: Springer Science & Business Media
Release Date: 2010-12-02
This volume presents the reader with a stimulating tapestry of essays exploring the nature of personal autonomy, self-determination, and agency, and their role in human optimal functioning at multiple levels of analysis from personal to societal and cross-cultural. The starting point for these explorations is self-determination theory, an integrated theory of human motivation and healthy development which has been under development for more than three decades (Deci & Ryan, 2000). As the contributions will make clear, psychological autonomy is a concept that forms the bridge between the dependence of human behavior on biological and socio-cultural determinants on the one side, and people’s ability to be free, reflective, and transforming agents who can challenge these dependencies, on the other. The authors within this volume share a vision that human autonomy is a fundamental pre-condition for both individuals and groups to thrive, and that without understanding the nature and mechanisms of autonomous agency vital social and human problems cannot be satisfactory addressed. This multidisciplinary team of researchers will collectively explore the nature of personal autonomy, considering its developmental origins, its expression within relationships, its importance within groups and organizational functioning, and its role in promoting to the democratic and economic development of societies. The book is aimed toward developmental, social, personality, and cross-cultural psychologists, towards researchers and practitioners’ in the areas of education, health and medicine, social work and, economics, and also towards all interested in creating a more sustainable and just world society through promoting individual freedom and agency. This volume will provide a theoretical and conceptual account of the nature and psychological mechanisms of personal motivational autonomy and human agency; richmultidisciplinary empirical evidence supporting the claims and propositions about the nature of human autonomy and capacities for self-regulation; explanations of how and why different psychological and socio-cultural conditions may play a role in promoting or undermining people’s autonomous motivation and well-being, discussions of how the promotion of human autonomy can positively influence environmental protection, democracy promotion and economic prosperity.