The text presents concepts of explainable artificial intelligence (XAI) in solving real world biomedical and healthcare problems. It will serve as an ideal reference text for graduate students and academic researchers in diverse fields of engineering including electrical, electronics and communication, computer, and biomedical. Present explainable artificial intelligence (XAI) based machine analytics and deep learning in medical science. Discusses explainable artificial intelligence (XA)I with the Internet of Medical Things (IoMT) for healthcare applications. Covers algorithms, tools, and frameworks for explainable artificial intelligence on medical data. Explores the concepts of natural language processing and explainable artificial intelligence (XAI) on medical data processing. Discusses machine learning and deep learning scalability models in healthcare systems. This text focusses on data driven analysis and processing of advanced methods and techniques with the help of explainable artificial intelligence (XAI) algorithms. It covers machine learning, Internet of Things (IoT), and deep learning algorithms based on XAI techniques for medical data analysis and processing. The text will present different dimensions of XAI based computational intelligence applications. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and biomedical engineering.

Social networking has increased drastically in recent years, resulting in an increased amount of data being created daily. Furthermore, diversity of issues and complexity of the social networks pose a challenge in social network mining. Traditional algorithm software cannot deal with such complex and vast amounts of data, necessitating the development of novel analytic approaches and tools. This reference work deals with social network aspects of big data analytics. It covers theory, practices and challenges in social networking. The book spans numerous disciplines like neural networking, deep learning, artificial intelligence, visualization, e-learning in higher education, e-healthcare, security and intrusion detection.

Discusses the industry transformation aligned with computerization of manufacturing and the concept of required skills needed to build the new workforce Covers the role of Artificial Intelligence in the management of resource flow and decision-making in the industrial transformation of operations and supply chain management Presents sustainability efficiency for industrial transformation with IoT, machine learning, data analysis and blockchain technologies Focuses on industrial development, design, implementation, and transformation using technologies such as Big Data Analytics, Blockchain among others Showcases the incorporation of complex processes and functions as one central component of digital systems Explores current trends that are accelerating the industrial transformation and influencing the transition of the fourth industrial revolution related to industrial infrastructure, biodiversity, and production enhancement

Social networking has increased drastically in recent years, resulting in an increased amount of data being created daily. Furthermore, diversity of issues and complexity of the social networks pose a challenge in social network mining. Traditional algorithm software cannot deal with such complex and vast amounts of data, necessitating the development of novel analytic approaches and tools. This reference work deals with social network aspects of big data analytics. It covers theory, practices and challenges in social networking. The book spans numerous disciplines like neural networking, deep learning, artificial intelligence, visualization, e-learning in higher education, e-healthcare, security and intrusion detection.