S. N. Kumar – författare

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.

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.

In this book, the role of Artificial Intelligence (AI), Internet of Things (IoT) and Blockchain in smart healthcare is explained through a detailed study of Artificial Neural Network, Fuzzy Set Theory, Intuitionistic Fuzzy Set, Machine Learning and Big Data technology.Industry 5.0 for Smart Healthcare Technologies: Utilizing Artificial Intelligence, Internet of Medical Things and Blockchain focuses on interesting applications of AI, promising advancements in IoT and important findings in Blockchain technology. When applied to smart healthcare technologies, Industry 5.0 offers numerous benefits that can revolutionize the healthcare industry. This book provides readers with insights and tools for enhanced patient care, remote patient monitoring, predictive analytics and early intervention of diseases, seamless data sharing and interoperability, telemedicine and virtual care, and a safer and more secure healthcare ecosystem. The authors examine novel computational algorithms for the processing of medical images, as well as novel algorithms for the processing of biosignals in detection of diseases. This book also explores systems for processing physiological parameters and discusses applications of AI techniques in the broader healthcare industry. The authors also investigate the importance of Augment Reality/Virtual Relatity (AR/VR) in the healthcare sector and examine the futuristic applications of Industry 5.0 in the healthcare sector.This book is intended for researchers and professionals working in interdisciplinary fields of computer engineering/science and healthcare. It will provide them with the tools to enhance diagnostics, optimize treatment plans, and empower patients to actively participate in their healthcare journey.

This book delves into the transformative potential of artificial intelligence (AI) and machine learning (ML) as game-changers in diagnosing and managing neurodisorder conditions. It covers a wide array of methodologies, algorithms, and applications in depth.Computational Intelligence Algorithms for the Diagnosis of Neurological Disorders equips readers with a comprehensive understanding of how computational intelligence empowers healthcare professionals in the fight against neurodisorders. Through practical examples and clear explanations, it explores the diverse applications of these technologies, showcasing their ability to analyze complex medical data, identify subtle patterns, and contribute to the development of more accurate and efficient diagnostic tools. The authors delve into the exciting possibilities of AI-powered algorithms, exploring their ability to analyze various data sources like neuroimaging scans, genetic information, and cognitive assessments. They also examine the realm of ML for pattern recognition, enabling the identification of early disease markers and facilitating timely intervention. Finally, the authors also address the critical challenges of data privacy and security, emphasizing the need for robust ethical frameworks to safeguard sensitive patient information.This book aims to spark a conversation and foster collaboration among researchers, clinicians, and technologists, and will assist radiologists and neurologists in making precise diagnoses with enhanced accuracy.

This book offers insights into how modern technologies are transforming agriculture with a focus on their effects in aiding sustainability. It explores the current applications of technologies such as AI, IoT, and machine learning, and their impact on improving crop yield, resource efficiency, and environmental impact. Through practical examples and case studies, it demonstrates how these technologies can address challenges in agriculture and enhance operational efficiency. Key Features:Analysis of how IoT devices and sensor networks are used for real-time monitoring of farm operations, soil conditions, and weather patterns.Studies emerging technologies like machine vision, predictive modelling, and natural language processing, for tasks such as crop monitoring and pest detection.Detailed discussion on machine learning algorithms, including supervised, unsupervised, and reinforcement learning, tailored for agricultural applications.Insights into how AI, IoT, and machine learning optimize resource use, improve crop yield and quality, and enhance sustainability.Case studies to highlight real-life examples from crop management to livestock and water conservation.Smart Agriculture for Sustainable Practices is for researchers, professionals, and policymakers interested in leveraging technology for sustainable agricultural practices.