Description
Knowledge Modelling and Big Data Analytics in Healthcare: Advances and Applications focuses on automated analytical techniques for healthcare applications used to extract knowledge from a vast 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.
The editors connect four contemporary areas of research rarely brought together in one book: artificial intelligence, big data analytics, knowledge modelling, and healthcare. They present 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.
Table of Contents
Section I: Big Data in Healthcare. 1. Healthcare Systems: A Design Overview of System and Technology. 2. An Overview of Big Data Applications in Healthcare: Opportunities and Challenges. 3. Clinical Decision Support Systems and Computational Intelligence for Healthcare Industry. 4. Proposed Intelligent Software System for Healthcare Systems using Machine Learning. Section II: Medical Imaging. 5. Diagnosis of Schizophrenia: A Study on Clinical and Computational Aspect. 6. Artificial Intelligence in Medical Imaging. 7. Integrated Neuroinformatics: Analytics and Application. 8. A Computer detection system (CDS) for fast and quick detection of lung cancer using Digital Image Processing. Section III: Computational Genomics. 9. Improved Prediction of Gene Expression of Epigenomics Data of Lung Cancer Using Machine Learning and Deep Learning Models. 10. Genetic Study of Schizophrenia and Role of Computational Genomics in Mental Healthcare. 11. Prediction of disease-lncRNA associations via Machine Learning and Big Data approaches. Section IV: Applications on Clinical Diagnosis. 12. On Tracking Slow modulations of Effective Connectivity for Early Detection of Epilepsy: Methods. 13. Application to Predict Type-II Diabetes using IoT Rural Healthcare Monitoring System. Section V: Issues in Security and Informatics in Healthcare. 14. A conceptual model for assessing security and privacy risks in healthcare information infrastructures: the CUREX approach. 15. Data science in health informatics.
