Computational Health Informatics for Biomedical Applications

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The recent explosion of technology in healthcare has rapidly changed the healthcare sector. Technologies such as Artificial Intelligence (AI) and Machine Learning (ML) along with the integration of the Internet of Medical Things have evolved to tackle the need for remote healthcare systems, augmenting them in a self-sustainable way. This new volume explores the many important smart technologies that can make healthcare delivery and monitoring faster, more efficient, and less invasive. It looks at computational tactics as applied to the development of biomedical applications using Artificial Intelligence, Machine Learning, signal analysis, computer-aided design, robotics and automation, biomedical imaging, telemedicine, and other technologies. The book provides a solid framework to give the modern class of medical gearheads information on the innovative applications of computational mechanisms for improving and expediting patient-friendly automation in healthcare. This review investigates the ramifications of computer-based intelligence on medical services the executives and difficulties associated with utilizing Artificial Intelligence (AI) in medical care alongside the audit of a few examination papers that pre-owned computer-based intelligence models in various areas of medical services like Dermatology, Radiology, Medication plan and so forth Computerized reasoning (man-made intelligence) intend to imitate human intellectual capacities. We study the current status of Artificial Intelligence (AI) applications in medical services and examine its future.

Author(s): Aryan Chaudhary, Sardar M. N. Islam (Naz)
Publisher: Apple Academic Press/CRC Press
Year: 2023

Language: English
Pages: 364

Cover
Half Title
Title Page
Copyright Page
Dedication
About the Editors
Table of Contents
Contributors
Abbreviations
Symbols
Foreword
Acknowledgments
Preface
1. IoT-Based Healthcare Systems and Their Security Concerns
2. Distributed Bragg Reflector Biosensor for Medical Applications
3. Photonic MEMS Sensor for Biomedical Applications
4. Chaotic and Nonlinear Features as EEG Biomarkers for the Diagnosis of Neuropathologies
5. Application of Artificial Intelligence and Deep Learning in Healthcare
6. Heart Disease Prediction Desktop Application Using Supervised Learning
7. Coronavirus Outbreak Prediction Analysis and Coronavirus Detection Through X-Ray Using Machine Learning
8. Numerical Analysis of Bioheat Transfer in Thermal Medicine
9. Evolution of Artificial Intelligence and Deep Learning in Healthcare
10. Medication Extender Drone Using CoppeliaSim
11. Big Data and Visualization-Oriented Latency-Aware Smart Health Architecture
12. Signal Processing in Biomedical Applications in Present and Future Development
13. Emerging Trends in Healthcare and Drug Development
14. Future Directions in Healthcare Research
Index