Machine Learning for Healthcare
Handling and Managing Data
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Product details:
- Edition number 1
- Publisher Chapman and Hall
- Date of Publication 9 December 2020
- ISBN 9780367352332
- Binding Hardback
- No. of pages222 pages
- Size 234x156 mm
- Weight 660 g
- Language English
- Illustrations 92 Illustrations, black & white; 21 Tables, black & white 178
Categories
Short description:
This book will provide in depth information about handling and managing healthcare data by Machine Learning methods. It will express the long-standing challenges in healthcare informatics and provide rational orientations on how to deal with them.
MoreLong description:
Machine Learning for Healthcare: Handling and Managing Data provides in-depth information about handling and managing healthcare data through machine learning methods. This book expresses the long-standing challenges in healthcare informatics and provides rational explanations of 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 in a case study which examines how chronic disease is being redefined through patient-led data learning and the Internet of Things. This text offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare. Readers will discover the ethical implications of machine learning in healthcare and the future of machine learning in population and patient health optimization. This book can also help assist in the creation of a machine learning model, performance evaluation, and the operationalization of its outcomes within organizations. It may appeal to computer science/information technology professionals and researchers working in the area of machine learning, and is especially applicable to the healthcare sector.
The features of this book include:
- A unique and complete focus on applications of machine learning in the healthcare sector.
- An examination of how data analysis can be done using healthcare data and bioinformatics.
- An investigation of how healthcare companies can leverage the tapestry of big data to discover new business values.
- An exploration of the concepts of machine learning, along with recent research developments in healthcare sectors.
Table of Contents:
Contents
Preface..................................................................................................................... vii
Acknowledgments..................................................................................................xi
Editors.................................................................................................................... xiii
List of Contributors............................................................................................. xvii
1. Fundamentals of Machine Learning...........................................................1
Rashmi Agrawal
2. Medical Information Systems..................................................................... 17
Uday Sah, Abhushan Chataut, and Jyotir Moy Chatterjee
3. The Role of Metaheuristic Algorithms in Healthcare...........................25
G. Uma Maheswari, R. Sujatha, V. Mareeswari, and E. P. Ephzibah
4. Decision Support System to Improve Patient Care................................ 41
V. Diviya Prabha and R. Rathipriya
5. Effects of Cell Phone Usage on Human Health and Specifically
on the Brain.....................................................................................................53
Soobia Saeed, Afnizanfaizal Abdullah, N. Z. Jhanjhi, Mehmood Naqvi
and Shakeel Ahmed
6. Feature Extraction and Bio Signals............................................................ 69
A. Mary Judith, S Baghavathi Priya, N. Kanya, and Jyotir Moy Chatterjee
7. Comparison Analysis of Multidimensional Segmentation Using
Medical Health-Care Information............................................................. 81
Soobia Saeed, Afnizanfaizal Abdullah, N. Z. Jhanjhi, Memood Naqvi,
and Azeem Khan
8. Deep Convolutional Network Based Approach for Detection
of Liver Cancer and Predictive Analytics on Cloud...............................95
Pramod H. B. and Goutham M.
9. Performance Analysis of Machine Learning Algorithm for
Healthcare Tools with High Dimension Segmentation...................... 115
Soobia Saeed, Afnizanfaizal Abdullah, N. Z. Jhanjhi, Memood Naqvi
and Mamoona Humayun
10. Patient Report Analysis for Identification and
Diagnosis of Disease.................................................................................. 129
Muralidharan C., Mohamed Sirajudeen Y., and Anitha R.
11. Statistical Analysis of the Pre- and Post-Surgery in the
Healthcare Sector Using High Dimension Segmentation.................. 159
Soobia Saeed, Afnizanfaizal Abdullah, N. Z. Jhanjhi, Memood Naqvi,
and Mamoona Humayun
12. Machine Learning in Diagnosis of Children with Disorders........... 175
Lokesh Kumar Saxena and Manishikha Saxena
13. Forecasting Dengue Incidence Rate in Tamil Nadu Using
ARIMA Time Series Model...................................................................... 187
S. Dhamodharavadhani, R. Rathipriya
Index......................................................................................................................203
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