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Mobile health technologies for ambient assisted living and healthcare
The use of telemedicine and mobile devices is growing, and sensors might aid in creating creative solutions. Developing these solutions is crucial for monitoring senior citizens, lifestyles, and medical procedures. The development of assistive technology for various users to follow sports and other activities is strongly tied to this study area. Data protection is crucial, and the development of these solutions for medical uses should be verified. The security and privacy of the information may be tied to other recognized research projects for their acceptability. ICT research has considerably improved quality of life and has fully assimilated all citizens into society through medical rehabilitation and assistive technology. The technologies and research fields that influence medical informatics include databases, networking, graphical user interfaces, data mining, machine learning, intelligent decision support systems, and specialized programming languages.
Integrated Risk and Vulnerability Management Assisted by Decision Support Systems : Relevance and Impact on Governance
This book includes terms of reference and offers an augmented volume of relevant work initiated within the comprehensive concept of “Knowledge Management and Risk Governance”.
Information and knowledge systems : Digital technologies, artificial intelligence and decision making ; 5th International Conference, ICIKS 2021, Virtual Event, June 22–23, 2021, Proceedings
This book constitutes the thoroughly refereed proceedings of the 5th International Conference on Information and Knowledge Systems, ICIKS 2021, which was held online during June 22-23, 2021. The International Conference on Information and Knowledge Systems (ICIKS 2021) gathered both researchers and practitioners in the fields of Information Systems, Artificial Intelligence, Knowledge Management and Decision Support. ICIKS seeks to promote discussions on various organizational, technological, and socio-cultural aspects of research in the design and use of information and knowledge systems in organizations.
Groupware : design, implementation, and use ; Vol. 3706 ; 11th International workshop, CRIWG 2005, Porto de Galinhas, Brazil, September 25-29, 2005, Proceedings
This book constitutes the refereed proceedings of the 11th International Workshop on Groupware, CRIWG 2005, held in Porto de Galinhas, Brazil in September 2005. The 16 revised full papers and 13 revised short papers presented together with a keynote paper were carefully reviewed and selected from 67 submissions. The papers are organized in topical sections on groupware development, collaborative applications, workflow management, knowledge management, computer supported collaborative learning, group decision support systems, mobile collaborative work, and work modeling in CSCW.
Groupware : Design, Implementation, and Use ; 14th International Workshop, CRIWG 2008, Omaha, NE, USA, September 14-18, 2008, Revised Selected Papers
This book constitutes the refereed post-conference proceedings of the 14th International Workshop on Groupware: Design, Implementation, and Use, held in Omaha, Nebraska, USA, during September 14-18, 2008.The 30 papers presented were carefully reviewed and selected from numerous submission. The topics covered are groupware solutions, co-located groups, groupware for health care, collaborative systems development, collaborative emergency response, groupware approaches, patterns of collaboration.
Groupware : Design, implementation, and use ; 13th International Workshop, CRIWG 2007, Bariloche, Argentina, September 16-20, 2007, Proceedings
This volume constitutes the proceedings of the 13th International Workshop on Groupware (CRIWG 2007). This workshop aims at providing a forum for academic researchers and professionals to exchange their experiences and their ideas about problems and solutions related to the design, development and use of groupware applications.
Fundamentals of Clinical Data Science
This book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare.
Enterprise Information Systems VII
The purpose of the 7th International Conference on Enterprise Information Systems (ICEIS) was to bring together researchers, engineers and practitioners interested in the advances and business applications of information systems. Five simultaneous tracks have been held, covering different aspects of Enterprise Information Systems Applications, including Enterprise Database Technology, Systems Integration, Artificial Intelligence, Decision Support Systems, Information Systems Analysis and Specification, Internet Computing, Electronic Commerce and Human Factors.
Enterprise Information Systems V
ICEIS focuses on real world applications and aims at bringing together researchers, engineers and practitioners interested in the advances and business applications of information systems. As in previous years, ICEIS’2003 held four simultaneous tracks covering different aspects of enterprise computing: Databases and Information Systems Integration, Artificial Intelligence and Decision Support Systems, Information Systems Analysis and Specification and Software Agents and Internet Computing. Although ICEIS’2003 received 546 paper submissions from over 50 countries, only 80 were accepted as full papers and presented in 30-minutes oral presentations. With an acceptance rate of 15%, these numbers demonstrate the intention of preserving a high quality forum for future editions of this conference. From the articles accepted as long papers for the conference, only 32 were selected for inclusion in this book Additional keynote lectures, tutorials and industrial sessions were also held during ICEIS’2003, and, for the first time this year, the 1st Doctoral Consortium on Enterprise Information Systems gave PhD students an opportunity to present their work to an international audience of experts in the field of information systems.
Designing and evaluating e-management decision tools : The integration of decision and negotiation models into internet-multimedia technologies
Presents the most relevant concepts for designing intelligent decision tools in an Internet-based multimedia environment and assessing the tools using concepts of statistical design of experiments. The book covers : Decision modeling paradigms , Visual interactive decision modeling , Online preference elicitation , collaborative decision making , negotiation and conflict resolution , marketing decision optimization , and guidelines for designing and evaluating decision support tools. This book is designed for the following uses: 1) for researchers and engineers, who are seeking recent advances and who are developing e-management systems; 2) for practitioners and managers, who seek insights about ICT potential and using ICT for business intelligence management; and 3) for students, who seek theoretical and practical concepts of building and evaluating prototype decision tools.
Decision Support for Global Enterprises
Decision Support for Global Enterprises consists of peer-reviewed and invited papers with two primary goals: (1) Stimulate creative discussion between academic researchers and the practitioner IS community to improve the research and practice in the area. (2) Increase awareness of the problems and challenges faced by global enterprises that can be met with innovative decision support systems. Limitations are also explored, covering the following topics: the emerging enterprise decision making processes and technologies; decision making in uncertain, changing conditions; the changing infrastructure in organizations and society; the expanding role of web technologies; and emerging theories and practices for managing knowledge and making decisions.
Data science for economics and finance : Methodologies and applications
The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis.
Data science and data analytics : Opportunities and challenges
Gives the concept of data science, tools, and algorithms that exist for many useful applications / Provides many challenges and opportunities in data science and data analytics that help researchers to identify research gaps or problems / Identifies many areas and uses of data science in the smart era / Applies data science to agriculture, healthcare, graph mining, education, security, etc.
Data Management Technologies and Applications ; 8th International Conference, DATA 2019, Prague, Czech Republic, July 26–28, 2019, Revised Selected Papers
This book constitutes the thoroughly refereed proceedings of the 8th International Conference on Data Management Technologies and Applications, DATA 2019, held in Prague, Czech Republic, in July 2019. The 8 revised full papers were carefully reviewed and selected from 90 submissions. The papers deal with the following topics: decision support systems, data analytics, data and information quality, digital rights management, big data, knowledge management, ontology engineering, digital libraries, mobile databases, object-oriented database systems, and data integrity.
Machine Learning and Probabilistic Graphical Models for Decision Support Systems
Presents recent advancements in research, a review of new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models, which are very effective techniques in gaining knowledge from Big Data and in interpreting decisions. It explores Bayesian network learning, Control Chart, Reinforcement Learning for multicriteria DSS, Anomaly Detection in Smart Manufacturing with Federated Learning, DSS in healthcare, DSS for supply chain management, etc. Researchers and practitioners alike will benefit from this book to enhance the understanding of machine learning, Probabilistic Graphical Models, and their uses in DSS in the context of decision making with uncertainty. The real-world case studies in various fields with guidance and recommendations for the practical applications of these studies are introduced in each chapter.
Machine Learning and Knowledge Extraction ; 5th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2021, Virtual Event, August 17–20, 2021, Proceedings
Constitutes the refereed proceedings of the 5th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2021, held in virtually in August 2021. The 20 full papers and 2 short papers presented were carefully reviewed and selected from 48 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity.
Biological and medical data analysis ; Vol. 4345 : 7th International Symposium, ISBMDA 2006, Thessaloniki, Greece, December 7-8, 2006. Proceeding
This book constitutes the refereed proceedings of the 7th International Symposium on Biological and Medical Data Analysis, ISBMDA 2006, held in Thessaloniki, Greece, December 2006. Coverage in this volume includes functional genomics, sequence analysis, biomedical models, information modeling, biomedical signal processing, biomedical image analysis, biomedical data analysis, as well as decision support systems and diagnostic tools.
Artificial intelligence in medicine ; 10th conference on artificial intelligence in medicine, AIME 2005, Aberdeen, UK, July 23-27, 2005, Proceedings
This book constitutes the refereed proceedings of the 10th Conference on Artificial Intelligence in Medicine in Europe, AIME 2005, held in Aberdeen, UK in July 2005. The 35 revised full papers and 34 revised short papers presented together with 2 invited contributions were carefully reviewed and selected from 148 submissions. The papers are organized in topical sections on temporal representation and reasoning, decision support systems, clinical guidelines and protocols, ontology and terminology, case-based reasoning, signal interpretation, visual mining, computer vision and imaging, knowledge management, machine learning, knowledge discovery, and data mining.
Artificial Intelligence Applications for Health Care
Covers topics on health care and artificial intelligence. Data sets related to biomedical signals (ECG, EEG, EMG) and images (X-rays, MRI, CT) are explored, analyzed, and processed through different computation intelligence methods. Applications of computational intelligence techniques like artificial and deep neural networks, swarm optimization, expert systems, decision support systems, clustering, and classification techniques on medial datasets are explained. Survey of medical signals, medial images, and computation intelligence methods are also provided.
Algorithms for Decision Making
A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them. Automated decision-making systems or decision-support systems—used in applications that range from aircraft collision avoidance to breast cancer screening—must be designed to account for various sources of uncertainty while carefully balancing multiple objectives. This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them.
