Next Generation Healthcare Systems Using Soft Computing Techniques
CRC Press (Verlag)
978-1-032-10799-8 (ISBN)
This book presents soft computing techniques and applications used in healthcare systems, along with the latest advancements. Written as a guide for assessing the roles that these techniques play, the book also highlights implementation strategies, lists problem-solving solutions, and paves the way for future research endeavors in smart and next-generation healthcare systems.
This book provides applications of soft computing techniques related to healthcare systems and can be used as a reference guide for assessing the roles that various techniques, such as machine learning, fuzzy logic, and statical mathematics, play in the advancements of smart healthcare systems. The book presents the basics as well as the advanced concepts to help beginners, as well as industry professionals, get up to speed on the latest developments in healthcare systems. The book examines descriptive, predictive, and social network techniques and discusses analytical tools and the important role they play in finding solutions to problems in healthcare systems. A framework of robust and novel healthcare techniques is highlighted, as well as implementation strategies and a setup for future research endeavors.
Healthcare Systems Using Soft Computing Techniques is a valuable resource for researchers and postgraduate students in healthcare systems engineering, computer science, information technology, and applied mathematics. The book introduces beginners to—and at the same time brings industry professionals up to speed with—the important role soft computing techniques play in smart healthcare systems.
1. Computational Intelligence for Healthcare. 2. Analysis of Recurrent Neural Network and Convolution Neural Network Techniques in Blood Cell Classification. Chapter 3. Evaluating the Effectiveness of the Convolution Neural Network in Detecting Brain Tumors. Chapter 4. Implementation of Machine Learning in Color Perception and Psychology: A Review. Chapter 5. Early Recognition of Dynamic Sleeping Patterns Associated with Rapid Eyeball Movement Sleep Behavior Disorder of Apnea Pateants Using Neural Network Techniques. Chapter 6. Smart Attendance cum Health Check-up Machine for Students/Villagers/Company Employees. Chapter 7. Oral Histopathological Photomicrograph Classification Using Deep Learning. Chapter 8. Prediction of Stage of Alzheimer's Disease DenseNet Deep Learning Model. Chapter 9. An Insight of Deep Learning Applications in the Healthcare Industry. Chapter 10. Expand Patient Care with AWS Cloud for Remote Medical Monitoring. Chapter 11. Privacy and Security Solution in Wireless Sensor Network for IoT in Healthcare System. Chapter 12. An Epileptic Seizure Detection and Classification Based on Machine Learning Techniques. Chapter 13. Analysis of Coronary Artery Disease Using Various Machine Learning Techniques.
| Erscheinungsdatum | 17.08.2022 |
|---|---|
| Reihe/Serie | Artificial Intelligence in Smart Healthcare Systems |
| Zusatzinfo | 38 Tables, black and white; 71 Line drawings, black and white; 25 Halftones, black and white; 96 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 410 g |
| Themenwelt | Medizin / Pharmazie ► Gesundheitswesen |
| ISBN-10 | 1-032-10799-5 / 1032107995 |
| ISBN-13 | 978-1-032-10799-8 / 9781032107998 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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