Knowledge Modelling and Big Data Analytics in Healthcare: Advances and Applications
- Length: 352 pages
- Edition: 1
- Language: English
- Publisher: CRC Press
- Publication Date: 2021-11-29
- ISBN-10: 0367696614
- ISBN-13: 9780367696610
- Sales Rank: #0 (See Top 100 Books)
This book focuses on automated analytical techniques for healthcare applications used to extract knowledge from a large amount of data. It brings together a variety of different aspects of the healthcare system and aids in the decision-making processes for healthcare professionals.
Knowledge Modelling and Big Data Analytics in Healthcare: Advances and Applications connects four contemporary areas of research rarely brought together in one book: artificial intelligence, big data analytics, knowledge modelling, and healthcare. It presents state-of-the-art research from the healthcare sector, including research on medical imaging, healthcare analysis, and the applications of artificial intelligence in drug discovery.
This book is intended for data scientists, academicians, and industry professionals in the healthcare sector.
Cover Page Half Title Page Title Page Copyright Page Contents Page Preface Page Editors Page Contributors Page Section I Big Data in Healthcare Chapter 1 Intelligent Healthcare Systems: A Design Overview of Existing Systems and Technologies Chapter 2 An Overview of Big Data Applications in Healthcare: Opportunities and Challenges Chapter 3 Clinical Decision Support Systems and Computational Intelligence for Healthcare Industries Chapter 4 Proposed Intelligent Software System for Healthcare Systems Using Machine Learning Section II Medical Imaging Chapter 5 Diagnosis of Schizophrenia: A Study on Clinical and Computational Aspects Chapter 6 Deep Learning in Medical Imaging Chapter 7 Integrated Neuroinformatics: Analytics and Application Chapter 8 A Fast and Reliable Detection System for Lung Cancer Using Image-Processing Techniques Section III Computational Genomics Chapter 9 Improved Prediction of Gene Expression of Epigenomics Data of Lung Cancer Using Machine Learning and Deep Learning Models Chapter 10 Genetic Study of Schizophrenia and Role of Computational Genomics in Mental Healthcare Chapter 11 Prediction of Disease–lncRNA Associations via Machine Learning and Big Data Approaches Section IV Applications in Clinical Diagnosis Chapter 12 Tracking Slow Modulations of Effective Connectivity for Early Epilepsy Detection: A Review Chapter 13 An Application for Predicting Type II Diabetes Using an IoT Healthcare Monitoring System Section V Issues in Security and Informatics in Healthcare Chapter 14 A Conceptual Model for Assessing Security and Privacy Risks in Healthcare Information Infrastructures: The CUREX Approach Chapter 15 Data Science in Health Informatics Index
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