This book explores the role of artificial Intelligence in Telemedicine. It explains the concepts through the detailed study and processing of biosignals, physiological parameters, and medical images. The book focuses on computational algorithms in telemedicine for the processing of biosignals, physiological parameters, and medical Images. The book is presented in two section.
The first section presents the role of computational algorithms in the processing of biosignal and medical images for disease diagnosis and treatment planning. Noise removal in ECG signal using an improved adaptive learning approach, classification of ECG signals using CNN for cardiac arrhythmia detection, EEG signal analysis for stroke detection, and EMG signal analysis for gesture classification were discussed in this section. Application of CNN in pertussis Diagnosis by temperature monitoring, physician handwriting recognition using deep learning model, melanoma detection using ABCD parameters, and transfer learning enabled heuristic approach for pneumonia detection was also discussed in this section
The second section focus on the role of IoT and artificial intelligence in the healthcare sector. IoT in smart health care and applications of artificial intelligence in disease diagnosis and prediction was discussed in this section. The importance of 5G/6G in the pandemic scenario for telemedicine applications, wireless capsule endoscopy image compression, leukemia detection from the microscopic cell images, and genomic signal processing using numerical mapping techniques was also discussed in this section.
This book can be used by a wide range of users including students, research scholars, faculty, and practitioners in the field of engineering for applications in biomedical signal, image analysis, and diagnosis.
PART 1 Biosignal and Medical Image Processing for Disease Diagnosis
Chapter 1 Lightweight One-Dimensional CNN for Cardiac Arrhythmia Classification
Chapter 2 An Automatic System for Pertussis Diagnosis with Temperature Monitoring Using CNN
Chapter 3 DocPresRec: Doctor’s Handwritten Prescription Recognition Using Deep Learning Algorithm
Chapter 4 An Efficient Deep Learning Approach for Brain Stroke Detection: Application of Telemedicine
Chapter 5 An Automated Detection of Notable ABCD Diagnostics of Melanoma in Dermoscopic Images
Chapter 6 Comparative Study of CNN and LSTM-Based Hand Gesture Classification Using EMG Signals
Chapter 7 Improved Transfer Learning-Enabled Heuristic Technique for Pneumonia Detection on Graphical Processing Unit Platform
Chapter 8 Improved Adaptive Learning Framework for an Effective Removal of Noise in ECG Signal for Telemedicine System
PART 2 Role of Artificial Intelligence and IoT in Health Care
Chapter 9 Human Disease Prediction System – Application of AI Techniques in Chronic Diseases
Chapter 10 Internet of Things in Mental Healthcare Worldwide – A Study
Chapter 11 Internet of Things: A Promise to Smart Healthcare
Chapter 12 A Brief Review on Wireless Capsule Endoscopy Image Compression
Chapter 13 A Comprehensive Review on Leukemia Diseases Based on Microscopic Blood Cell Images
Chapter 14 Effects of Numerical Mapping Techniques on Performance in Genomic Signal Processing
Chapter 15 Importance of 5G/6G in Telemedicine System during the Pandemic Situation
Chapter 16 Applications of Artificial Intelligence Techniques in Healthcare
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