Knowledge Modelling and Big Data Analytics in Healthcare Advances and Applications

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.

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.

Mayuri Mehta is a passionate learner, teacher and researcher. She is working as a Professor in the Department of Computer Engineering, Sarvajanik College of Engineering and Technology, Surat, India. She received her Ph.D. in Computer Engineering from Sardar Vallabhbhai National Institute of Technology (SVNIT), India. Her areas of teaching and research include Data Science, Machine Learning & Deep Learning, Health Informatics, Computer Algorithms, and Python Programming. She has worked on several academic assignments in collaboration with professors of universities across the globe. Her 20 years of professional experience includes several academic and research achievements along with administrative and organizational capabilities. She has also co-edited a book titled "Tracking and Preventing Diseases using Artificial Intelligence". With the noble intention of applying her technical knowledge for societal impact, she is working on several research projects in the Healthcare domain in association with doctors doing private practice and doctors of Medical Colleges, which reflect her research outlook. She is an active member of professional bodies such as IEEE, Computer Society of India (CSI) and Indian Society for Technical Education (ISTE).

Kalpdrum Passi received his Ph.D. in Parallel Numerical Algorithms from Indian Institute of Technology, Delhi, India in 1993. He is an Associate Professor, Department of Mathematics & Computer Science, at Laurentian University, Ontario, Canada. He has published many papers on Parallel Numerical Algorithms in international journals and conferences. He has collaborative work with faculty in Canada and US and the work was tested on the CRAY XMP’s and CRAY YMP’s. He transitioned his research to web technology, and more recently has been involved in machine learning and data mining applications in bioinformatics, social media and other data science areas. His research in bioinformatics has been on impr