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Smart Distributed Embedded Systems for Healthcare Applications
Smart Distributed Embedded Systems for Healthcare ApplicationsНазвание: Smart Distributed Embedded Systems for Healthcare Applications
Автор: Preeti Nagrath, Jafar A. Alzubi, Bhawna Singla
Издательство: CRC Press
Серия: Explainable AI (XAI) for Engineering Applications
Год: 2023
Страниц: 199
Язык: английский
Формат: pdf (true)
Размер: 17.7 MB

This book discusses the applications and optimization of emerging smart technologies in the field of healthcare. It further explains different modeling scenarios of the latest technologies in the healthcare system and compares the results to better understand the nature and progress of diseases in the human body, which would ultimately lead to early diagnosis and better treatment and cure of diseases with the help of distributed technology.

Embedded systems is the smart integration of hardware and software, which has many applications. Initially, embedded systems were introduced in the field of healthcare to cater to medical issues. Now, the amalgamation of smart distributed embedded systems with digital technologies such as Artificial Intelligence (AI), cloud computing, IOT, NLP, augmented reality, virtual reality, and fog computing are used, and they prove to be a boon in the field of health and medicine. The new features offered by smart distributed technologies have accelerated the growth in the health industry.

This book provides in-depth comprehensive information on the latest research in the area of health and medicine on smart distributed embedded technologies. Chapter 1, “Healthcare Engineering Using AI and Distributed Technologies”, discusses the transformation of healthcare with distributed computing. The chapter highlights the impact, challenges, benefits, and limitations of AI in the healthcare industry. The chapter also features AI-based robots in the healthcare ecosystem.

Chapter 2, “Cloud Computing in Healthcare: A Systematic Study”, elaborates on medicinal solutions provided by cloud computing using cloud-based molecular simulation tools and cloud-based medical imaging solutions. Application of fog computing in healthcare is also discussed.

Chapter 3, “Medical Information Extraction of Clinical Notes and Pictorial Visualization of Electronic Medical Records Summary Interface”, highlights the NLP technique that enables users to quickly fetch and comprehend the patient’s medical history and current data using Open NLP-trained Time-Entity model.

Chapter 4, “Investigations on RFID-Enabled Healthcare Usage and Adoption Issues”, highlights that RFID has the potential for monitoring, tracking, and storing read data in real time. The chapter discusses various advantages provided by RFID technology. When RFID is linked, it can provide valuable process-integrated decision support based on current medical knowledge. It can also use patient data for research and healthcare reporting in a variety of ways. The chapter anticipates an RFID-enabled smart hospital in the future, which will combine RFID and wireless technology to provide a variety of healthcare services.

Covers the implementation models using technologies such as Artificial Intelligence, Machine Learning, and Deep Learning with distributed systems for better diagnosis and treatment of diseases.

Gives in-depth review of technological advancements like advanced sensing technologies such as plasmonic sensors, usage of RFIDs, and electronic diagnostic tools in the field of healthcare engineering.

Discusses possibilities of augmented reality and virtual reality interventions for providing unique solutions in medical science, clinical research, psychology, and neurological disorders.

Highlights the future challenges and risks involved in the application of smart technologies such as cloud computing, fog computing, IOT, and distributed computing in healthcare.

Confers to utilize the AI and ML and associated aids in healthcare sectors in the post-Covid 19 period to revitalize the medical setup.

Contributions included in the book will motivate technological developers and researchers to develop new algorithms and protocols in the healthcare field. It will serve as a vast platform for gaining knowledge regarding healthcare delivery, health- care management, healthcare in governance, and health monitoring approaches using distributed environments. It will serve as an ideal reference text for graduate students and researchers in diverse engineering fields including electrical, electronics and communication, computer, and biomedical fields.

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