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" Data science for healthcare : "
Sergio Consoli, Diego Reforgiato Recupero, Milan Petković, editors.
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BL
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| Record Number
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860551
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| Title & Author
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Data science for healthcare : : methodologies and applications /\ Sergio Consoli, Diego Reforgiato Recupero, Milan Petković, editors.
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| Publication Statement
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Cham, Switzerland :: Springer,, 2019.
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| Page. NO
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1 online resource (xii, 367 pages) :: illustrations (some color)
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| ISBN
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3030052494
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: 9783030052492
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3030052486
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3030052508
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9783030052485
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9783030052508
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| Contents
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Intro; Foreword; Preface; Aim; Organization; Audience; Final Words; Contents; Part I Challenges and Basic Technologies; Data Science in Healthcare: Benefits, Challenges and Opportunities; 1 Introduction and Preliminaries; 2 Healthcare Opportunities; 2.1 Economic Potential; 2.2 Technical and Organizational Challenges; 3 Opportunities with Most Impact; 3.1 Healthy Living: Prevention and Health Promotion; 3.1.1 Lifestyle Support; 3.1.2 Better Understanding of Triggers of Chronic Diseases for Effective Early Detection; 3.1.3 Population Health; 3.1.4 Infectious Diseases; 3.2 Healthcare
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3.2.1 Precision Medicine3.2.2 Collecting Patient-Reported Outcomes and Total Pathway Costs for Value-Based Healthcare; 3.2.3 Optimizing Workflows in Healthcare; 3.2.4 Infection Prevention, Prediction and Control; 3.2.5 Social-Clinical Care Path; 3.2.6 Patient Support and Involvement; 3.2.7 Shared Decision Support; 3.2.8 Home Care; 3.2.9 Clinical Research; 3.3 Healthcare Data Stewardship Challenges; 4 Privacy, Ethics and Security; 5 Technology Landscape; 5.1 Technical Challenges; 5.1.1 Data Quality; 5.1.2 Data Quantity; 5.1.3 Multimodal Data; 5.1.4 Data Access; 5.1.5 Patient-Generated Data
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5.1.6 Usability/Deployment Methodology5.2 Platforms, Services and Infrastructures; 5.2.1 High-Performance Computers and Exascale Computing; 5.2.2 Infrastructure; 5.2.3 Data Integration; 5.2.4 Interoperability Standards; 5.3 Data Analytics; 5.3.1 Advanced Machine Learning and Reinforcement Learning; 5.3.2 Deep Learning; 5.3.3 Real-Time Analytics; 5.3.4 Clinical Reasoning; 5.3.5 End User-Driven Data Analytics; 5.3.6 Natural Language Processing and Text Analytics; 5.3.7 Knowledge-Based Approaches; 5.3.8 High-Performance Genome Analysis; 5.3.9 Understanding and Reliability in Analytics
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5.4 Example Success Stories6 Conclusions and Recommendations; References; Introduction to Classification Algorithms and Their Performance Analysis Using Medical Examples; 1 Introduction; 2 Naive Bayesian Classification; 2.1 Mathematical Background; 2.2 Skewing Factors and Terms; 2.3 Additional Details of NBC; 3 Performance Analysis; 3.1 Confusion Matrix and Performance Metrics; 3.2 Accuracy and Its Limitations; 3.3 Operating Conditions; 3.4 Dependency of Class Skew; 3.5 ROC Space; 3.6 Expected Cost; 3.7 Iso-Cost Curves; 3.8 ROC Curves; 3.9 Area Under the Curve; 3.10 Precision-Recall Space
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| Abstract
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This book seeks to promote the exploitation of data science in healthcare systems. The focus is on advancing the automated analytical methods used to extract new knowledge from data for healthcare applications. To do so, the book draws on several interrelated disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies, and focuses on their direct application to healthcare. Building on three tutorial-like chapters on data science in healthcare, the following eleven chapters highlight success stories on the application of data science in healthcare, where data science and artificial intelligence technologies have proven to be very promising. This book is primarily intended for data scientists involved in the healthcare or medical sector. By reading this book, they will gain essential insights into the modern data science technologies needed to advance innovation for both healthcare businesses and patients. A basic grasp of data science is recommended in order to fully benefit from this book.
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| Subject
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Artificial intelligence-- Medical applications.
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Medical informatics.
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Artificial intelligence-- Medical applications.
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Medical informatics.
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| Dewey Classification
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610.285
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| LC Classification
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R858
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| Added Entry
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Consoli, Sergio
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Petković, Milan
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Reforgiato Recupero, Diego
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