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Recent advancements in medical technology, such as telehealth services, have influenced the healthcare sector tremendously. While telehealth technology and its application are not new, it has not been widely utilized despite the numerous benefits and opportunities it provides. However, recent policy changes have lowered obstacles to telehealth access and pushed the use of telemedicine to deliver acute, chronic, primary, and specialist care. In order to successfully integrate this technology in all areas of healthcare, further study is required to fully understand the best practices and challenges of adoption. Advancement, Opportunities, and Practices in Telehealth Technology discusses advances in the digital health technology and telemedicine domains as well as key challenges, solutions, and opportunities regarding their use in healthcare. The book also introduces critical communication protocols, interconnections, system designs, and developments that are extensively used in the present-day telehealth process. Covering a wide range of topics such as digital twins, big data analytics, and robotics, this reference work is an ideal resource for engineers, industry professionals, hospital administration, policymakers, researchers, scholars, academicians, practitioners, instructors, and students.
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.
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