Название: Healthcare Systems and Health Informatics: Using Internet of ThingsАвтор: Pawan Singh Mehra, Lalit Mohan Goyal, Arvind Dagur
Издательство: CRC Press
Год: 2022
Страниц: 267
Язык: английский
Формат: pdf (true)
Размер: 15.2 MB
This book covers the fundamentals of IoT and healthcare systems for carrying out system architectures, protocols, wearable devices, and interoperability. It explores major challenges in AI and smart computing in resource-constrained IoT-based applications along with cost, energy efficiency, and the availability of quality service.
Healthcare Systems and Health Informatics: Using the Internet of Things explores the role of Artificial Intelligence and Smart Computing in health informatics and healthcare with an emphasis on clinical data management and analysis for precise prediction and prompt action. It presents cutting-edge tracking, monitoring, real-time assistance, and security for IoT in healthcare and discusses broadly wearable sensors and IoT devices and their role in smart living assistance. The book goes onto describing a system model and architecture for a clear picture of energy conservation-based IoT in healthcare and explains the challenges and opportunities with IoT-based healthcare industries. A study of the threats and impacts along with the need for information security is also included.
IT- enabled tools such as the Internet of Things (IoT), Artificial Intelligence (AI), Big Data analysis are contributing a lot in promoting the healthcare industry. Exceptionally the IoT has been enforced extensively to integrate the current healthcare industry resources for offering reliable, efficient, and agile medical services to aged patients and patients with continual illness. Besides, IoT has various utilisations in the medical field, such as safeguarding and monitoring patients and improving patients’ care. Thus, IoT ensures enhanced care for patients by facilitating them to spend extra time with the medical practitioners. With the help of data collected by IoT, doctors can comprehend patient’s physical condition better and react as a result. The collected data permits doctors to observe patients’ physical condition and warning signs and address problems with no delay. For these kinds of matters, neural network- enabled data analytics works better along with the vast usage of IoT.
Customized medicine or personalized medicine (PH) is a new approach to patient care aimed at changing the conventional health system. Advanced patient data gathers wearable IoT (the Internet of Things), sensor devices and mobile devices from electronic health records, web- based information and social media. The healthcare system uses Machine Learning, AI techniques to collect datasets of disease point identification and auto- management of patient compliance and clinical intervention. For the last few decades AI has been very useful towards each and every aspects of our lifestyle which leads many progress of humankind.
Artificial Intelligence (AI) also can significantly contribute to predicting drug metabolism and toxicity. Machine- deep learning (ML/ DL) approaches are especially useful in taking up the work in this area. ML/ DL are commonly used to synchronize analytical and silico models simultaneously. The models cover multiple service applications and help patients’ clinical decisions to support their wellbeing. These analyse the data obtained from sensors and other sources to detect patient behavioural trends and clinical conditions. These models, for example, evaluate information gathered to assess the progress and behaviours of the patient. Here we will mention the test dataset and the training dataset for the efforts made in understanding drug metabolism and toxicity using AI techniques and patients’ compliance. Based on the user knowledge, the input feed, the training dataset could be generated.
Chapters written by experts in the field, this book provides a comprehensive description of the important aspects of IoT and Health from a beginner to advance level perspective and is ideal for researchers, academicians, students, persons in industry, technologists, and entrepreneurs.
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