Machine Learning for Healthcare: Handling and Managing Data book will provide in depth information about handling and managing healthcare data by Machine Learning methods. This book will express the long-standing challenges in healthcare informatics and provide rational orientations on how to deal with them.
Machine Learning for Healthcare: Handling and Managing Data provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of machine learning applications. These are illustrated through how chronic disease is being redefined through patient-led data learning and the Internet of things. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in health care. One will discover the ethical implications of machine learning in health care and the future of machine learning in population and patient health optimization. One can also create a machine learning model, evaluate performance, and operationalize its outcomes within organizations. This book can be used by Computer Science/ Information Technology Professionals / Researchers working in this area of Machine Learning especially applicable on healthcare sector.
The Features of this book are:
- A unique book completely focusing on applications of Machine Learning in Healthcare sector.
- Book is focused on how data analysis can be done using healthcare data & bioinformatics using healthcare data.
- Book investigates how healthcare companies can leverage the tapestry of big data to discover new business value,
- Book will explore the concepts of Machine Learning along with the recent research development in Health care sectors.
Table of Contents
Chapter 1- Fundamentals of Machine Learning (Rashmi Agrawal)
Chapter 2- Medical Information System (Uday Sah, Abhushan Chataut, Jyotir Moy Chatterjee)
Chapter 3- Role of Metaheuristic Algorithm in Healthcare (G. Uma Maheswari, R. Sujatha, V. Mareeswari, E. P. Ephzibah)
Chapter 4- Decision Support System to Improve Patient Care (V. Diviya Prabha, R. Rathipriya)
Chapter 5- Effects of Cell Phone usage on Human health specifically on the Brain (Soobia Saeed, Afnizanfaizal Abdullah, NZ Jhanjhi, Mehmood Naqvi, Shakeel Ahmed)
Chapter 6-Feature Extraction and Applications of Bio Signals (Mary Judith A., S. Baghavathi Priya, N. Kanya, Jyotir Moy Chatterjee)
Chapter 7- Comparison Analysis of Multidimensional Segmentation (Soobia Saeed, Afnizanfaizal Abdullah, NZ Jhanjhi, Memood Naqvi, Azeem Khan)
Chapter 8-Deep Convolutional Network Based Approach for Detection of Liver Cancer and Predictive Analytics on Cloud (Pramod H. B., Goutham M.)
Chapter 9-Performance Analysis of Machine Learning Algorithm for Health Care Tools with High Dimension Segmentation (Soobia Saeed, Afnizanfaizal Abdullah, NZ Jhanjhi, Memood Naqvi, Mamoona Humayun)
Chapter 10-Patient Report Analysis for Identification and Diagnosis of Disease (Muralidharan C., Mohamed Sirajudeen Y., Anitha R.)
Chapter 11-Statistical Analysis the Pre- Surgery and Post-Surgery of Health Care Sector Using High Dimension Segmentation (Soobia Saeed, Afnizanfaizal Abdullah, NZ Jhanjhi, Memood Naqvi, Mamoona Humayun)
Chapter 12- Machine Learning in Diagnosis of Children with Disorders (Lokesh Kumar Saxena, Manishikha Saxena)
Chapter 13-Forecasting Dengue Incidence Rate in Tamil Nadu using ARIMA Time Series Model (S. Dhamodharavadhani, R. Rathipriya)
Dac-Nhuong Le is Ph.D, Deputy-Head of Faculty of Information Technology, Haiphong University, Vietnam. Vice-Director of Information Technology Apply Center in the same university. He is a research scientist of Research and Development Center of Visualization & Simulation in (CSV), Duy Tan University, Danang, Vietnam. He has more than 45 publications in the reputed international conferences, journals and online book chapter contributions (Indexed By: SCI, SCIE, SSCI, Scopus, ACM, DBLP). His area of research includes: evaluation computing and approximate algorithms, network communication, security and vulnerability, network performance analysis and simulation, cloud Computing, image processing in biomedical. His core work in network security, wireless, soft computing, mobile computing and biomedical. Recently, he has been the technique program committee, the technique reviews, the track chair for international conferences Jyotir Moy Chatterjee is currently working as an Assistant Professor of IT department at LBEF (Asia Pacific University of Technology & Innovation), Kathmandu, Nepal. Prior to that he worked as an Assistant Professor in CSE department at GD Rungta College of Engineering & Technology (CSVTU), Bhilai, Chhattisgarh, India. He has completed M. Tech in Computer Science & Engineering from Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha and B. Tech in Computer Science & Engineering from Dr. MGR Educational & Research Institute, Chennai. He is having 33 publications (3 SCIE indexed, 1 SCI indexed, 1 ESCI indexed, 1 ACMDL indexed, 1 Web of Science indexed, 23 UGC indexed, 2 International Conference, 1 authored book, 2 Scopus indexed book chapter). His research interest includes the Cloud Computing, Big Data, Privacy Preservation, Data Mining, Internet of Things, Machine Learning. Abhishek Kumar Pandey is pursuing his Doctorate in computer science from University of Madras and got enrolled in 2015 session and researching on face recognition using IOT concept and completed M. Tech in Computer Sci. & Engineering from Government engineering college Ajmer, Rajasthan Technical University, Kota India. He is working as an Assistant Professor of Computer Science at Aryabhatt Engineering College and Research centre, Ajmer and also visiting faculty in Government University MDS Ajmer. Rashmi Agrawal is working as Professor in Department of Computer Applications in MRIIRS, Faridabad. She has a rich teaching experience of more than 17 years. She is UGC-NET(CS) qualified.