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Author: Finn V. Jensen
Publisher: Springer
Published: 1997-08-15
Total Pages: 178
ISBN-13: 9780387915029
DOWNLOAD EBOOKDisk contains: Tool for building Bayesian networks -- Library of examples -- Library of proposed solutions to some exercises.
Author: Richard E. Neapolitan
Publisher: Prentice Hall
Published: 2004
Total Pages: 704
ISBN-13:
DOWNLOAD EBOOKIn this first edition book, methods are discussed for doing inference in Bayesian networks and inference diagrams. Hundreds of examples and problems allow readers to grasp the information. Some of the topics discussed include Pearl's message passing algorithm, Parameter Learning: 2 Alternatives, Parameter Learning r Alternatives, Bayesian Structure Learning, and Constraint-Based Learning. For expert systems developers and decision theorists.
Author: Chakraborty, Chinmay
Publisher: IGI Global
Published: 2019-02-22
Total Pages: 448
ISBN-13: 1522577971
DOWNLOAD EBOOKMedical and information communication technology professionals are working to develop robust classification techniques, especially in healthcare data/image analysis, to ensure quick diagnoses and treatments to patients. Without fast and immediate access to healthcare databases and information, medical professionals’ success rates and treatment options become limited and fall to disastrous levels. Advanced Classification Techniques for Healthcare Analysis provides emerging insight into classification techniques in delivering quality, accurate, and affordable healthcare, while also discussing the impact health data has on medical treatments. Featuring coverage on a broad range of topics such as early diagnosis, brain-computer interface, metaheuristic algorithms, clustering techniques, learning schemes, and mobile telemedicine, this book is ideal for medical professionals, healthcare administrators, engineers, researchers, academicians, and technology developers seeking current research on furthering information and communication technology that improves patient care.
Author: Bibudhendu Pati
Publisher: Springer Nature
Published:
Total Pages: 693
ISBN-13: 9819950155
DOWNLOAD EBOOKAuthor: Guoliang Li
Publisher: Springer
Published: 2019-04-23
Total Pages: 616
ISBN-13: 3030185907
DOWNLOAD EBOOKThis book constitutes the workshop proceedings of the 24th International Conference on Database Systems for Advanced Applications, DASFAA 2019, held in Chiang Mai, Thailand, in April 2019. The 14 full papers presented were carefully selected and reviewed from 26 submissions to the three following workshops: the 6th International Workshop on Big Data Management and Service, BDMS 2019; the 4th International Workshop on Big Data Quality Management, BDQM 2019; and the Third International Workshop on Graph Data Management and Analysis, GDMA 2019. This volume also includes the short papers, demo papers, and tutorial papers of the main conference DASFAA 2019.
Author: B. S.P. Mishra
Publisher: Springer
Published: 2016-02-05
Total Pages: 199
ISBN-13: 3319275208
DOWNLOAD EBOOKThis volume is aiming at a wide range of readers and researchers in the area of Big Data by presenting the recent advances in the fields of Big Data Analysis, as well as the techniques and tools used to analyze it. The book includes 10 distinct chapters providing a concise introduction to Big Data Analysis and recent Techniques and Environments for Big Data Analysis. It gives insight into how the expensive fitness evaluation of evolutionary learning can play a vital role in big data analysis by adopting Parallel, Grid, and Cloud computing environments.
Author: Qingsheng Zhu
Publisher: World Scientific
Published: 2005-10-07
Total Pages: 1009
ISBN-13: 9814479136
DOWNLOAD EBOOKThis book presents the latest techniques, algorithms, research accomplishments and trend in computer science and engineering. It collects together 222 peer reviewed papers presented at the 11th Joint International Computer Conference. The theme of this year is “IT: Intellectual Capital for the Betterment of Human Life”. The articles in this book cover a wide range of active and interesting areas such as Digital Entertainment, Grid Computing, Embedded System, Web Service and Knowledge Engineering. This book serves as a good reference not only for researchers but also for graduate students in corresponding fields.The proceedings have been selected for coverage in:•Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings)•CC Proceedings — Engineering & Physical Sciences
Author: Marco Scutari
Publisher: CRC Press
Published: 2021-07-28
Total Pages: 275
ISBN-13: 1000410382
DOWNLOAD EBOOKExplains the material step-by-step starting from meaningful examples Steps detailed with R code in the spirit of reproducible research Real world data analyses from a Science paper reproduced and explained in detail Examples span a variety of fields across social and life sciences Overview of available software in and outside R
Author: Dubey, Archi
Publisher: IGI Global
Published: 2024-07-18
Total Pages: 468
ISBN-13:
DOWNLOAD EBOOKThe healthcare industry is increasingly complex, demanding personalized treatments and efficient operational processes. Traditional research methods need help to keep pace with these demands, often leading to inefficiencies and suboptimal outcomes. Integrating digital twin technology presents a promising solution to these challenges, offering a virtual platform for modeling and simulating complex healthcare scenarios. However, the full potential of digital twins still needs to be explored mainly due to a lack of comprehensive guidance and practical insights for researchers and practitioners. Exploring the Advancements and Future Directions of Digital Twins in Healthcare 6.0 is not just a theoretical exploration. It is a practical guide that bridges the gap between theory and practice, offering real-world case studies, best practices, and insights into personalized medicine, real-time patient monitoring, and healthcare process optimization. By equipping you with the knowledge and tools needed to effectively integrate digital twins into your healthcare research and operations, this book is a valuable resource for researchers, academicians, medical practitioners, scientists, and students.
Author: M.I. Jordan
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 658
ISBN-13: 9401150141
DOWNLOAD EBOOKIn the past decade, a number of different research communities within the computational sciences have studied learning in networks, starting from a number of different points of view. There has been substantial progress in these different communities and surprising convergence has developed between the formalisms. The awareness of this convergence and the growing interest of researchers in understanding the essential unity of the subject underlies the current volume. Two research communities which have used graphical or network formalisms to particular advantage are the belief network community and the neural network community. Belief networks arose within computer science and statistics and were developed with an emphasis on prior knowledge and exact probabilistic calculations. Neural networks arose within electrical engineering, physics and neuroscience and have emphasised pattern recognition and systems modelling problems. This volume draws together researchers from these two communities and presents both kinds of networks as instances of a general unified graphical formalism. The book focuses on probabilistic methods for learning and inference in graphical models, algorithm analysis and design, theory and applications. Exact methods, sampling methods and variational methods are discussed in detail. Audience: A wide cross-section of computationally oriented researchers, including computer scientists, statisticians, electrical engineers, physicists and neuroscientists.
