Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare, Chang, Mark

Автор: Kleinberg, Samantha (stevens Institute Of Technology, New Jersey)
Название: Causality, probability, and time
ISBN: 1107686016 ISBN-13(EAN): 9781107686014
Издательство: Cambridge Academ
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Цена: 40130.00 T
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Описание: This book presents a new approach to causal inference (finding relationships from a set of data) and explanation (assessing why a particular event occurred), addressing both the timing and complexity of relationships. The practical use of the method developed is illustrated through theoretical and experimental case studies, demonstrating its feasibility and success.

Автор: Hand
Название: Artificial Intelligence Frontiers in Statistics
ISBN: 0412407108 ISBN-13(EAN): 9780412407109
Издательство: Taylor&Francis
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Цена: 183750.00 T
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Описание: This book presents a summary of recent work on the interface between artificial intelligence and statistics

Автор: G. Della Riccia; R. Kruse; R. Viertl
Название: Proceedings of the ISSEK94 Workshop on Mathematical and Statistical Methods in Artificial Intelligence
ISBN: 3211827137 ISBN-13(EAN): 9783211827130
Издательство: Springer
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Цена: 81050.00 T
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Описание: An important part of the Artificial Intelligence theory is concerned with reasoning based on uncertain information. Classical logic and probability theory are not adequate for this, and many formalisms have been developed. The proceedings contained here aim to contribute to the elucidation of similarities and differences between these formalisms.

Автор: Giulianella Coletti; Didier Dubois; R. Scozzafava
Название: Mathematical Models for Handling Partial Knowledge in Artificial Intelligence
ISBN: 0306450763 ISBN-13(EAN): 9780306450761
Издательство: Springer
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Цена: 149530.00 T
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Описание: Petr Hajek shows that reasoning in fuzzy logic may be put on a strict logical (formal) basis, so contributing to our understanding of what fuzzy logic is and what one is doing when applying fuzzy reasoning.

Автор: Tshilidzi Marwala
Название: Artificial Intelligence Techniques for Rational Decision Making
ISBN: 3319382985 ISBN-13(EAN): 9783319382982
Издательство: Springer
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Цена: 79190.00 T
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Описание:

Introduction to Rational Decision Making.- Casual Function for Rational Decision Making: Application to Militarized Interstate Disputes.- Correlation Function for Rational Decision Making: Application to Epileptic Activity.- Missing Data Approaches for Rational Decision Making: Application to Anecdotal Data.- Rational Counterfactuals and Decision Making: Application to Interstate Conflict.- Flexibility-Bounded Rationality in Interstate Conflict.- Filtering Irrelevant Information for Rational Decision Making.- Group Decision Making.- Conclusion.- Appendix A: Fourier Transform, Wavelet Transform, Modal Properties and Pseudo-Modal Energies.- Appendix B: Committee of Networks.

Автор: Tshilidzi Marwala
Название: Artificial Intelligence Techniques for Rational Decision Making
ISBN: 3319114239 ISBN-13(EAN): 9783319114231
Издательство: Springer
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Цена: 79190.00 T
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Описание: Artificial Intelligence Techniques for Rational Decision Making

Автор: Paris
Название: Pure Inductive Logic
ISBN: 1107042305 ISBN-13(EAN): 9781107042308
Издательство: Cambridge Academ
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Цена: 141510.00 T
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Описание: This book establishes pure inductive logic as a contemporary branch of mathematical logic. Collecting together research from a wide range of sources within one unified context, it provides both a comprehensive account of the subject up to cutting-edge modern research, and an accessible reference for the philosopher or computer scientist.

Автор: Guy Lebanon; Mohamed El-Geish
Название: Computing with Data
ISBN: 331998148X ISBN-13(EAN): 9783319981482
Издательство: Springer
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Цена: 93160.00 T
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Описание: This book introduces basic computing skills designed for industry professionals without a strong computer science background. Written in an easily accessible manner, and accompanied by a user-friendly website, it serves as a self-study guide to survey data science and data engineering for those who aspire to start a computing career, or expand on their current roles, in areas such as applied statistics, big data, machine learning, data mining, and informatics.The authors draw from their combined experience working at software and social network companies, on big data products at several major online retailers, as well as their experience building big data systems for an AI startup. Spanning from the basic inner workings of a computer to advanced data manipulation techniques, this book opens doors for readers to quickly explore and enhance their computing knowledge.Computing with Data comprises a wide range of computational topics essential for data scientists, analysts, and engineers, providing them with the necessary tools to be successful in any role that involves computing with data. The introduction is self-contained, and chapters progress from basic hardware concepts to operating systems, programming languages, graphing and processing data, testing and programming tools, big data frameworks, and cloud computing.The book is fashioned with several audiences in mind. Readers without a strong educational background in CS--or those who need a refresher--will find the chapters on hardware, operating systems, and programming languages particularly useful. Readers with a strong educational background in CS, but without significant industry background, will find the following chapters especially beneficial: learning R, testing, programming, visualizing and processing data in Python and R, system design for big data, data stores, and software craftsmanship.

Автор: Danel Jaso
Название: Pattern Recognition Techniques, Technology & Applications
ISBN: 1681174642 ISBN-13(EAN): 9781681174648
Издательство: Gazelle Book Services
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Цена: 217350.00 T
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Описание: This book highlights recent advances and new ideas in promoting the techniques, technology and applications of pattern recognition. The book provides a comprehensive overview of the developments of techniques and approaches on pattern recognition. Pattern recognition is the science of making inferences from perceptual data, using tools from statistics, probability, computational geometry, machine learning, signal processing, and algorithm design. A wealth of advanced pattern recognition algorithms are emerging from the interdiscipline between technologies of effective visual features and the human-brain cognition process. Effective visual features are made possible through the rapid developments in appropriate sensor equipments, novel filter designs, and viable information processing architectures. While the understanding of human-brain cognition process broadens the way in which the computer can perform pattern recognition task. Pattern recognition is the imposition of identity on input data, such as speech, images, or a stream of text, by the recognition and delineation of patterns it contains and their relationships. Stages in pattern recognition may involve measurement of the object to identify distinguishing attributes, extraction of features for the defining attributes, and comparison with known patterns to determine a match or mismatch. Pattern recognition has extensive application in astronomy, medicine, robotics, and remote sensing by satellites.

Автор: Rafalski, Edward M. | Mu
Название: Healthcare Analytics
ISBN: 1138196363 ISBN-13(EAN): 9781138196360
Издательство: Taylor&Francis
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Цена: 36740.00 T
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Описание: This is a comprehensive, practical guide which looks at the advantages and limitations of new data analysis techniques being introduced across public health and administration services.

Автор: Holmgren, Eric B.
Название: Theory of Drug Development
ISBN: 1138374687 ISBN-13(EAN): 9781138374683
Издательство: Taylor&Francis
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Цена: 63280.00 T
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Описание:

Theory of Drug Development presents a formal quantitative framework for understanding drug development that goes beyond simply describing the properties of the statistics in individual studies. It examines the drug development process from the perspectives of drug companies and regulatory agencies.

By quantifying various ideas underlying drug development, the book shows how to systematically address problems, such as:

• Sizing a phase 2 trial and choosing the range of p-values that will trigger a follow-up phase 3 trial
• Deciding whether a drug should receive marketing approval based on its phase 2/3 development program and recent experience with other drugs in the same clinical area
• Determining the impact of adaptive designs on the quality of drugs that receive marketing approval
• Designing a phase 3 pivotal study that permits the data-driven adjustment of the treatment effect estimate
• Knowing when enough information has been gathered to show that a drug improves the survival time for the whole patient population

Drawing on his extensive work as a statistician in the pharmaceutical industry, the author focuses on the efficient development of drugs and the quantification of evidence in drug development. He provides a rationale for underpowered phase 2 trials based on the notion of efficiency, which leads to the identification of an admissible family of phase 2 designs. He also develops a framework for evaluating the strength of evidence generated by clinical trials. This approach is based on the ratio of power to type 1 error and transcends typical Bayesian and frequentist statistical analyses.

Автор: Harry Yang, Steven Novick
Название: Bayesian Analysis with R for Drug Development: Concepts, Algorithms, and Case Studies
ISBN: 1138295876 ISBN-13(EAN): 9781138295872
Издательство: Taylor&Francis
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Цена: 93910.00 T
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Описание: Few books deal with issues faced by researchers in the areas of pre-clinical animal studies, analytical method and process development, manufacturing control, the implementation of Bayesian applications for pharmaceutical problems, using modern computational tools such as R. This book does.