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Computational Methods in Psychiatry
This book presents a particular area of interest in computing psychiatry with the modelling of mood and anxiety disorders. It highlights various methods for building these models. Clinical applications are prevalent due to the growth and interaction of these multiple approaches. Besides, it outlines some original predictive and computational modelling ideas for enhancing psychological treatment interventions. Computational psychiatry combines multiple levels and types of computation with different data types to improve mental illness understanding, prediction, and treatment.
Modeling, Control and Drug Development for COVID-19 Outbreak Prevention
This book is well-structured book which consists of 31 full chapters. The book chapters' deal with the recent research problems in the areas of modeling, control and drug development, and it presents various techniques of COVID-19 outbreak prevention modeling. The book also concentrates on computational simulations that may help speed up the development of drugs to counter the novel coronavirus responsible for COVID-19. This is an open access book.
Predictive Analytics of Psychological Disorders in Healthcare
This book discusses an interdisciplinary field which combines two major domains: healthcare and data analytics. It presents research studies by experts helping to fight discontent, distress, anxiety and unrealized potential by using mathematical models, machine learning, artificial intelligence, etc. and take preventive measures beforehand. Psychological disorders and biological abnormalities are significantly related with the applications of cognitive illnesses which has increased significantly in contemporary years and needs rapid investigation. The research content of this book is helpful for psychological undergraduates, health workers and their trainees, therapists, medical psychologists, and nurses.
Predictive and Preventive Measures for Covid-19 Pandemic
This book explores the inputs with regard to individuals and companies who have developed technologies and innovative solutions, bioinformatics, datasets, apps for diagnosis, etc., that can be leveraged for strengthening the fight against coronavirus. It focuses on technology solutions to stop Covid-19 outbreak and mitigate the risk. The book contains innovative ideas from active researchers who are presently working to find solutions, and they give insights to other researchers to explore the innovative methods and predictive modeling techniques. The novel applications and techniques of established technologies like artificial intelligence (AI), Internet of things (IoT), big data, computer vision and machine learning are discussed to fight the spread of this disease, Covid-19. This pandemic has triggered an unprecedented demand for digital health technology solutions and unleashing information technology to win over this pandemic.
Intelligent Computing and Networking
This book gathers high-quality peer-reviewed research papers presented at the International Conference on Intelligent Computing and Networking (IC-ICN 2022), organized by the Computer Department, Thakur College of Engineering and Technology, in Mumbai, Maharashtra, India, on February 25–26, 2022. The book includes innovative and novel papers in the areas of intelligent computing, artificial intelligence, machine learning, deep learning, fuzzy logic, natural language processing, human–machine interaction, big data mining, data science and mining, applications of intelligent systems in healthcare, finance, agriculture and manufacturing, high-performance computing, computer networking, sensor and wireless networks, Internet of Things (IoT), software-defined networks, cryptography, mobile computing, digital forensics and blockchain technology.
Information and Communication Technology (ICT) Frameworks in Telehealth
This book aims to explore technology solutions and systems to help people in remote areas in order to improve medical care. Access to health care services is critical to good health, but residents of remote areas face a variety of access barriers. The obstacles faced by health care providers and patients in rural areas are very different from those in urban areas. This could be caused by economic factors, cultural and social differences, educational deficiencies, lack of recognition by legislators, and the sheer isolation of living in inland areas, all of which conspire to create health care disparities and hinder people living in inland areas in their struggle to lead normal, healthy lives....
Influential Machines
A new framework for understanding how algorithms influence Web applications offer us conclusions about science. Twitter bots generate art. Machine-learning systems satirize politicians. We live in an era where a substantial share of our private and public communication is machinic. Modern computing machines cannot yet speak for themselves—although the capacities of AI are rapidly expanding—but they generate rhetorical energies as they give advice, entertain, and proffer insight, speaking to human concerns in more-than-human ways and guiding human action. In Influential Machines Miles C. Coleman looks beyond human communication to interrogate the ways in which the machines and algorithms ...
Medical Data Analysis and Processing using Explainable Artificial Intelligence
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. Presents 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 la...
Predictive Modeling in Biomedical Data Mining and Analysis
Predictive Modeling in Biomedical Data Mining and Analysis presents major technical advancements and research findings in the field of machine learning in biomedical image and data analysis. The book examines recent technologies and studies in preclinical and clinical practice in computational intelligence. The authors present leading-edge research in the science of processing, analyzing and utilizing all aspects of advanced computational machine learning in biomedical image and data analysis. As the application of machine learning is spreading to a variety of biomedical problems, including automatic image segmentation, image classification, disease classification, fundamental biological pro...
