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Recently, researchers have focused on challenging problems facing the development of data warehousing, knowledge discovery, and data mining applications.
Technology is changing the practice of healthcare by the ways medical information is stored, shared, and accessed. With mobile innovations, new strategies are unfolding to further advance processes and procedures in medical settings. Next-Generation Mobile and Pervasive Healthcare Solutions is an advanced reference source for the latest research on emerging progress and applications within mobile health initiatives and health informatics. Featuring coverage on a broad range of topics and perspectives such as electronic health records (EHR), clinical decision support systems, and medical ontologies, this publication is ideally designed for professionals and researchers seeking scholarly material on the increased use of mobile health applications.
There are many different approaches to understanding human consciousness. By conducting research to better understand various biological mechanisms, these can be redefined and utilized for technological purposes. Advanced Research on Biologically Inspired Cognitive Architectures is an essential reference source for the latest scholarly research on the biological elements of human cognition and examines the applications of consciousness within computing environments. Featuring exhaustive coverage on a broad range of innovative topics and perspectives, such as artificial intelligence, bio-robotics, and human-computer interaction, this publication is ideally designed for academics, researchers, professionals, graduate students, and practitioners seeking current research on the exploration of the intricacies of consciousness and different approaches of perception.
Decision support systems (DSS) are widely touted for their effectiveness in aiding decision making, particularly across a wide and diverse range of industries including healthcare, business, and engineering applications. The concepts, principles, and theories of enhanced decision making are essential points of research as well as the exact methods, tools, and technologies being implemented in these industries. From both a standpoint of DSS interfaces, namely the design and development of these technologies, along with the implementations, including experiences and utilization of these tools, one can get a better sense of how exactly DSS has changed the face of decision making and management in multi-industry applications. Furthermore, the evaluation of the impact of these technologies is essential in moving forward in the future. The Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering explores how decision support systems have been developed and implemented across diverse industries through perspectives on the technology, the utilizations of these tools, and from a decision management standpoint. The chapters will cover not only the interfaces, implementations, and functionality of these tools, but also the overall impacts they have had on the specific industries mentioned. This book also evaluates the effectiveness along with benefits and challenges of using DSS as well as the outlook for the future. This book is ideal for decision makers, IT consultants and specialists, software developers, design professionals, academicians, policymakers, researchers, professionals, and students interested in how DSS is being used in different industries.
With the advent of new technologies in big data science, the study of medical problems has made significant progress. Connecting medical studies and computational methods is crucial for the advancement of the medical industry. Big Data Analytics in HIV/AIDS Research provides emerging research on the development and implementation of computational techniques in big data analysis for biological and medical practices. While highlighting topics such as deep learning, management software, and molecular modeling, this publication explores the various applications of data analysis in clinical decision making. This book is a vital resource for medical practitioners, nurses, scientists, researchers, and students seeking current research on the connections between data analytics in the field of medicine.
The medical profession requires extensive training and preparation in order to ensure the success and competency of future doctors and healthcare professionals. With an emphasis on professional development and medical education, current professionals in this field acknowledge the importance of residency programs and training in the professional development of future doctors. Optimizing Medicine Residency Training Programs presents a comprehensive overview of chapters ranging from the history of medicine to opportunities and research for further exploration geared toward the professional development and medical training for the next generation of doctors and healthcare professionals. This publication is an essential reference source for academicians, practitioners, and professionals interested in the education and training of modern medical professionals.
"This book explores the complex relationships between patients, physicians, and nurses with different cultural backgrounds, integrating theoretical and empirical perspectives on medical teamwork"--
The process of patient education allows for patients to think about their health in new ways and for educators and professionals to propose new ways to heal, with the ultimate goal of patients having a positive outlook on life and consistently maintained health. Innovative Collaborative Practice and Reflection in Patient Education presents multigenre writing, incorporating authors' personal and professional stories along with academic theories. It combines the fields of education and medicine, presenting innovative approaches to health education and designing new approaches to healing. This research publication will impact the field of health education and be of use to educators, researchers, practitioners, professionals, and patients.
Data Warehousing and Knowledge Discovery have been widely accepted as key te- nologies for enterprises and organizations as a means of improving their abilities in data analysis, decision support, and the automatic extraction of knowledge from data. With the exponentially growing amount of information to be included in the decision making process, the data to be processed is becoming more and more complex in both structure and semantics. Consequently, the process of retrieval and knowledge disc- ery from this huge amount of heterogeneous complex data constitutes the reality check for research in the area. During the past few years, the International Conference on Data Warehousing and Knowledge Discovery (DaWaK) has become one of the most important international scientific events to bring together researchers, developers and practitioners. The DaWaK conferences serve as a prominent forum for discussing the latest research issues and experiences in developing and deploying data warehousing and knowledge discovery systems, applications, and solutions. This year’s conference, the 10th Int- national Conference on Data Warehousing and Knowledge Discovery (DaWaK 2008), continued the tradition of facilitating the cross-disciplinary exchange of ideas, expe- ence and potential research directions. DaWaK 2008 sought to disseminate innovative principles, methods, algorithms and solutions to challenging problems faced in the development of data warehousing, knowledge discovery and data mining applications.
This book constitutes the refereed proceedings of the 19th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2017, held in Lyon, France, in August 2017. The 24 revised full papers and 11 short papers presented were carefully reviewed and selected from 97 submissions. The papers are organized in the following topical sections: new generation data warehouses design; cloud and NoSQL databases; advanced programming paradigms; non-functional requirements satisfaction; machine learning; social media and twitter analysis; sentiment analysis and user influence; knowledge discovery; and data flow management and optimization.