Modeling Decision Artificial Intelligence (33 results)

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Paperback or Softback. Condition: New. Artificial Intelligence in Healthcare: Clinical Decision Support and Modeling 1.97. Book.

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Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher.

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Taschenbuch. Condition: Neu. Neuware - The field of healthcare is being transformed by artificial intelligence (AI). Professionals need to comprehend the potential impact of AI on clinical decision support and epidemiological modeling. This comprehensive guide helps bridge the gap between theory and practice, providing readers with the knowledge and skills needed to leverage AI in healthcare.The book covers a broad range of topics, from the basics of AI and machine learning to the creation and assessment of clinical decision support systems. It also covers the use of state-of-the-art AI methods for disease surveillance and outbreak prediction. Through a mix of theoretical explanations, practical examples, and hands-on exercises, readers will learn how to prepare and manipulate clinical and epidemiological datasets, build, and implement cutting-edge AI solutions, and address the ethical considerations and challenges of applying AI in healthcare.What makes this book unique is its combination of expert insights from a practitioner's perspective, real-world case studies, and a practical approach to walk readers through the process of developing and implementing AI solutions. Additional online resources, like datasets, code samples, and case studies, further enrich the learning experience.Whether you are a healthcare professional looking to enhance patient outcomes, a data scientist striving to create innovative AI solutions, or a student eager to explore the frontiers of healthcare technology, this book is an essential resource.

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Taschenbuch. Condition: Neu. Neuware - This book constitutes the proceedings of the 8th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2011, held in Changsha, China, in July 2011.The 25 papers presented were carefully reviewed and selected from 43 submissions. The volume also contains extended abstracts of the three invited papers. The topics covered are aggregation operators and decision making; clustering and similarity; computational intelligence; and data privacy.

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Paperback. Condition: new. Paperback. This book gathers selected and peer-reviewed contributions presented at the 18th Conference of the International Federation of Classification Societies (IFCS 2024), held in San Jose, Costa Rica, July 1519, 2024. Covering a wide range of topics, it describes modern methods and real-world applications in data science, classification, and artificial intelligence related to modeling decision making.Numerous novel techniques and innovative applications are investigated, such as anomaly detection in public procurement processes, multivariate functional data clustering, air pollution prediction, benchmark generation for probabilistic planning, recommendation systems based on symbolic data analysis, and methods for clustering mixed-type data. Advanced statistical concepts are explored, including Vapnik-Chervonenkis dimensionality, Riemannian statistics, hypothesis testing for interval-valued data, and mixed models. Furthermore, machine learning techniques are applied to predict soil bacterial and fungal communities, classify electoral behavior and political competition, and assess corrosion degradation in mining pipelines.The diversity of topics discussed in this collection reflects the ongoing advancement and interdisciplinary nature of statistical and data science research, as well as its application across various fields and sectors. These studies contribute to the development of robust methodologies and efficient computational tools to address complex challenges in the era of big data. The book is intended for researchers and practitioners seeking the latest developments and applications in the field of data science and classification. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book gathers selected and peer-reviewed contributions presented at the 18th Conference of the International Federation of Classification Societies (IFCS 2024), held in San José, Costa Rica, July 15 19, 2024. Covering a wide range of topics, it describes modern methods and real-world applications in data science, classification, and artificial intelligence related to modeling decision making.Numerous novel techniques and innovative applications are investigated, such as anomaly detection in public procurement processes, multivariate functional data clustering, air pollution prediction, benchmark generation for probabilistic planning, recommendation systems based on symbolic data analysis, and methods for clustering mixed-type data. Advanced statistical concepts are explored, including Vapnik-Chervonenkis dimensionality, Riemannian statistics, hypothesis testing for interval-valued data, and mixed models. Furthermore, machine learning techniques are applied to predict soil bacterial and fungal communities, classify electoral behavior and political competition, and assess corrosion degradation in mining pipelines.The diversity of topics discussed in this collection reflects the ongoing advancement and interdisciplinary nature of statistical and data science research, as well as its application across various fields and sectors. These studies contribute to the development of robust methodologies and efficient computational tools to address complex challenges in the era of big data. The book is intended for researchers and practitioners seeking the latest developments and applications in the field of data science and classification.

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Paperback. Condition: new. Paperback. This book gathers selected and peer-reviewed contributions presented at the 18th Conference of the International Federation of Classification Societies (IFCS 2024), held in San Jose, Costa Rica, July 1519, 2024. Covering a wide range of topics, it describes modern methods and real-world applications in data science, classification, and artificial intelligence related to modeling decision making.Numerous novel techniques and innovative applications are investigated, such as anomaly detection in public procurement processes, multivariate functional data clustering, air pollution prediction, benchmark generation for probabilistic planning, recommendation systems based on symbolic data analysis, and methods for clustering mixed-type data. Advanced statistical concepts are explored, including Vapnik-Chervonenkis dimensionality, Riemannian statistics, hypothesis testing for interval-valued data, and mixed models. Furthermore, machine learning techniques are applied to predict soil bacterial and fungal communities, classify electoral behavior and political competition, and assess corrosion degradation in mining pipelines.The diversity of topics discussed in this collection reflects the ongoing advancement and interdisciplinary nature of statistical and data science research, as well as its application across various fields and sectors. These studies contribute to the development of robust methodologies and efficient computational tools to address complex challenges in the era of big data. The book is intended for researchers and practitioners seeking the latest developments and applications in the field of data science and classification. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Paperback. Condition: new. Paperback. This book gathers selected and peer-reviewed contributions presented at the 18th Conference of the International Federation of Classification Societies (IFCS 2024), held in San Jose, Costa Rica, July 1519, 2024. Covering a wide range of topics, it describes modern methods and real-world applications in data science, classification, and artificial intelligence related to modeling decision making.Numerous novel techniques and innovative applications are investigated, such as anomaly detection in public procurement processes, multivariate functional data clustering, air pollution prediction, benchmark generation for probabilistic planning, recommendation systems based on symbolic data analysis, and methods for clustering mixed-type data. Advanced statistical concepts are explored, including Vapnik-Chervonenkis dimensionality, Riemannian statistics, hypothesis testing for interval-valued data, and mixed models. Furthermore, machine learning techniques are applied to predict soil bacterial and fungal communities, classify electoral behavior and political competition, and assess corrosion degradation in mining pipelines.The diversity of topics discussed in this collection reflects the ongoing advancement and interdisciplinary nature of statistical and data science research, as well as its application across various fields and sectors. These studies contribute to the development of robust methodologies and efficient computational tools to address complex challenges in the era of big data. The book is intended for researchers and practitioners seeking the latest developments and applications in the field of data science and classification. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Softcover. Condition: New. Dust Jacket Condition: no dj. First. Modeling Decision Processes Using Artificial Intelligence Simulations is a practical guide that offers a systematic approach to modeling decision processes using artificial intelligence simulations. By leveraging the principles of artificial intelligence and machine learning, readers will learn how to develop and implement effective decision-making models, including tools and techniques for data analysis, model selection, and decision-making. This book provides a comprehensive framework for developing a decision-making model that can simulate real-world decision-making processes, including tools and methods for data collection, model calibration, and model validation. By applying the principles outlined in this book, readers can develop a more nuanced understanding of decision-making processes and improve their ability to make informed decisions. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Fast-track conference proceedings State-of-the-art research Up-to-date resultsThis book constitutes the proceedings of the 8th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2011, held in Changsha, .

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The growing complexity of public issues makes policy-making a major challenge, in a context where decision-makers are still too often dependent on macro-level information. This book contributes to decision making by exploring the micro environment of the decision-making process. This multidisciplinary approach lies at the crossroads of decision analysis, complex systems, modeling and simulation, and artificial intelligence. It constitutes a paradigmatic and methodological transition in the field of public policy that has led to the development of a decision-making diagnostic model (PODESIM), based on data exploitation and simulation. This methodological innovation provides a new overview of the decision-making environment, more detailed and more constructed than the linear and deterministic vision of the classical approaches. Finally, it proposes to make the fields of public policy and management benefit from the integration of various disciplines through the introduction of computational techniques and data mining for a digital transformation of governance.