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Sharma A Exploration Of Artificial Intelligence And Blockchain Technology 2024
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This book offers in-depth reviews of different techniques and novel approaches of using blockchain and Artificial Intelligence (AI) in smart healthcare services. The volume brings 14 reviews and research articles written by academicians, researchers and industry professionals to give readers a current perspective of smart healthcare solutions for medical and public health services. The book starts with examples of how blockchain can be applied in healthcare services such as the care of osteoporosis patients and security. Several chapters review AI models for disease detection including breast cancer, colon cancer and anemia. The authors have included model design and parameters for the benefit of professionals who want to implement specific algorithms. Furthermore, the book also includes chapters on IoT frameworks for smart healthcare systems, giving readers a primer on how to utilize the technology in this sector. Additional use cases for Machine Learning for gesture learning, and sentiment analysis. From the last decade onward, a considerable amount of research and developments in technology have taken place especially in the healthcare industry, with the involvement of technologies like Artificial Intelligence (AI), Machine Learning (ML), Deep Learning, Blockchain, Communication Systems, Internet of Things, Multisensory Systems, etc. The purpose is only to make smart and secure healthcare possible. Machine Learning techniques and algorithms are required to give a boost to the aim of smart healthcare. Hence, to fulfill the vision of smart healthcare, the tools and applications based on Artificial Intelligence and Machine Learning are becoming extremely popular for producing more accuracy (in terms of values) in predicting results (without being explicitly programmed) in the healthcare industry. However, Artificial Intelligence-based algorithms are quite helpful for the transformation of physiological data into clinical information of real values, but for processing such big data from a set of medical images and identifying or extracting characteristic patterns of health function, then translating these patterns into clinical information definitely requires an adequate knowledge base of physiology, advanced digital signal processing capabilities, and Machine Learning. The domain of Artificial Intelligence can be taken into three main groups viz. Artificial Slight Intellect, Artificial Overall Intelligence, and Artificial Super Intelligence, and undoubtedly all these groups work in an absolute manner in the presence of fundamental or advanced Machine Learning techniques. There are a number of categories existing concerning the AI/ML algorithms used for fulfilling the objective of smart healthcare such as supervised (regression, decision-tree, classification) and unsupervised (clustering, association analysis, hidden Markov model, etc.). Although the preparation of intelligent algorithms or systems based on AI/ML combined with novel wearable portable devices (especially sensors etc.) offers unprecedented possibilities and opportunities for remote patient monitoring, traditional sharing schemes cannot guarantee the security and immutability of data. Machine Learning along with Artificial Intelligence is quite helpful towards the research and development in health care, but still lacking somewhat especially in security and privacy related to healthcare information of all categories i.e. the dream of smart healthcare is far behind. So to make the dream of smart healthcare come true, the emerging Blockchain technology is spreading its feet in the healthcare industry having revolutionized results. The Blockchain is helping in numerous perspectives in health care such that for managing the security, the integrity of data i.e. electronic health records (EHRs), electronic medical records (EMRs); preserving immutability of data, tracking the origin, spreading of data, the authenticity of data, data sharing, protection against data spoofing, etc., as compared to traditional security mechanism i.e. a single technology having a number of features. In simple words, smart healthcare will only be possible if both the accuracy in results, security and privacy of such results will be equally maintained. In a nutshell, the primary goal of this book is to offer a variety of techniques for a broad readership, ranging from computing and methodologies to business analytics in the health sciences. Readership: Academic, professional, and students affiliated institutions involved in digital transformation in the healthcare sector
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