Acm Bcb17

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Multimodal Analytics for Next-Generation Big Data Technologies and Applications

Author : Kah Phooi Seng
Publisher : Springer
ISBN 13 : 3319975986
Total Pages : 391 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Multimodal Analytics for Next-Generation Big Data Technologies and Applications by : Kah Phooi Seng

Download or read book Multimodal Analytics for Next-Generation Big Data Technologies and Applications written by Kah Phooi Seng and published by Springer. This book was released on 2019-07-18 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book will serve as a source of reference for technologies and applications for multimodality data analytics in big data environments. After an introduction, the editors organize the book into four main parts on sentiment, affect and emotion analytics for big multimodal data; unsupervised learning strategies for big multimodal data; supervised learning strategies for big multimodal data; and multimodal big data processing and applications. The book will be of value to researchers, professionals and students in engineering and computer science, particularly those engaged with image and speech processing, multimodal information processing, data science, and artificial intelligence.

Algorithms and Methods in Structural Bioinformatics

Author : Nurit Haspel
Publisher : Springer Nature
ISBN 13 : 303105914X
Total Pages : 120 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Algorithms and Methods in Structural Bioinformatics by : Nurit Haspel

Download or read book Algorithms and Methods in Structural Bioinformatics written by Nurit Haspel and published by Springer Nature. This book was released on 2022-09-01 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-dimensional structure and function of molecules present many challenges and opportunities for developing an understanding of biological systems. With the increasing availability of molecular structures and the advancing accuracy of structure predictions and molecular simulations, the space for algorithmic advancement on many analytical and predictive problems is both broad and deep. To support this field, a rich set of methods and algorithms are available, addressing a variety of important problems such as protein-protein interactions, the effect of mutations on protein structure and function, and protein structure determination. Despite recent advancements in the field, in particular in protein folding with the development of AlphaFold, many problems still remain unsolved. In this book we focus on a number of topics in Structural Bioinformatics: Cryo-EM structural detection, protein conformational exploration, elucidation of molecular binding surface using geometry, the effect of mutations, insertions and deletions on protein structural stability, and protein-ligand binding.

Trends in Deep Learning Methodologies

Author : Vincenzo Piuri
Publisher : Academic Press
ISBN 13 : 0128232684
Total Pages : 308 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Trends in Deep Learning Methodologies by : Vincenzo Piuri

Download or read book Trends in Deep Learning Methodologies written by Vincenzo Piuri and published by Academic Press. This book was released on 2020-11-12 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters elaborate on these models which have shown significant success in dealing with massive data for a large number of applications, given their capacity to extract complex hidden features and learn efficient representation in unsupervised settings. Chapters investigate deep learning-based algorithms in a variety of application, including biomedical and health informatics, computer vision, image processing, and more. In recent years, many powerful algorithms have been developed for matching patterns in data and making predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. Deep learning methods can deal with multiple levels of representation in which the system learns to abstract higher level representations of raw data. Earlier, it was a common requirement to have a domain expert to develop a specific model for each specific application, however, recent advancements in representation learning algorithms allow researchers across various subject domains to automatically learn the patterns and representation of the given data for the development of specific models. - Provides insights into the theory, algorithms, implementation and the application of deep learning techniques - Covers a wide range of applications of deep learning across smart healthcare and smart engineering - Investigates the development of new models and how they can be exploited to find appropriate solutions

Graph Embedding Methods for Multiple-Omics Data Analysis

Author : Chen Qingfeng
Publisher : Frontiers Media SA
ISBN 13 : 2889716007
Total Pages : 220 pages
Book Rating : 4.8/5 (897 download)

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Book Synopsis Graph Embedding Methods for Multiple-Omics Data Analysis by : Chen Qingfeng

Download or read book Graph Embedding Methods for Multiple-Omics Data Analysis written by Chen Qingfeng and published by Frontiers Media SA. This book was released on 2021-11-08 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Real-World Evidence of Natural Products, Herbal Medicines, and Traditional Chinese Medicine Treatments

Author : Liyun He
Publisher : Frontiers Media SA
ISBN 13 : 2832552218
Total Pages : 259 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Real-World Evidence of Natural Products, Herbal Medicines, and Traditional Chinese Medicine Treatments by : Liyun He

Download or read book Real-World Evidence of Natural Products, Herbal Medicines, and Traditional Chinese Medicine Treatments written by Liyun He and published by Frontiers Media SA. This book was released on 2024-07-25 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: The concept of real-world studies (RWS) has emerged in recent years and differs from randomized controlled trials (RCTs) in design and implementation. The importance of real-world data (RWD) and real-world evidence (RWE) in the context of medical and health decision-making is rising. This is relevant for the many and diverse medical traditions globally. RWS can bring new ideas and methodologies for clinical efficacy and safety evaluation of different specific preparations used in a Traditional Medicine (TM) and allow a high-quality assessment of the evidence for specific uses of such preparations. TM, including Traditional Chinese medicine (TCM), Traditional European Medicine (TEM) or Traditional Indian Medicines (TIM) as well as interventions using herbal medicines or natural products such as dietary fibre are all examples of practices which can benefit from RWS. For example, TCM is a unique form of medical practice based on a complex philosophy as well as on real-world clinical experience and evidence. RWE is essential for understanding the evidence one can derive from the outcomes of medical practice. It is of particular interest for understanding TCM diagnosis and treatment. In addition, there is potential for real-world traditional medical therapies based on other cultural and philosophical principles (natural products or herbal medicines). Currently, RWS is mostly utilized for evaluation the clinical efficacy of Traditional medicine (TM) treatments, including post-marketing re-evaluation of new medications or traditional classical prescriptions, as well as TM-related mechanistic research.

Intelligent Data Engineering and Analytics

Author : Vikrant Bhateja
Publisher : Springer Nature
ISBN 13 : 9811975248
Total Pages : 627 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Intelligent Data Engineering and Analytics by : Vikrant Bhateja

Download or read book Intelligent Data Engineering and Analytics written by Vikrant Bhateja and published by Springer Nature. This book was released on 2023-02-23 with total page 627 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents the proceedings of the 10th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2022), held at NIT Mizoram, Aizawl, Mizoram, India during 18 – 19 June 2022. Researchers, scientists, engineers, and practitioners exchange new ideas and experiences in the domain of intelligent computing theories with prospective applications in various engineering disciplines in the book. These proceedings are divided into two volumes. It covers broad areas of information and decision sciences, with papers exploring both the theoretical and practical aspects of data-intensive computing, data mining, evolutionary computation, knowledge management and networks, sensor networks, signal processing, wireless networks, protocols and architectures. This volume is a valuable resource for postgraduate students in various engineering disciplines.

Synthetic Data for Deep Learning

Author : Sergey I. Nikolenko
Publisher : Springer Nature
ISBN 13 : 3030751783
Total Pages : 348 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Synthetic Data for Deep Learning by : Sergey I. Nikolenko

Download or read book Synthetic Data for Deep Learning written by Sergey I. Nikolenko and published by Springer Nature. This book was released on 2021-06-26 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book on synthetic data for deep learning, and its breadth of coverage may render this book as the default reference on synthetic data for years to come. The book can also serve as an introduction to several other important subfields of machine learning that are seldom touched upon in other books. Machine learning as a discipline would not be possible without the inner workings of optimization at hand. The book includes the necessary sinews of optimization though the crux of the discussion centers on the increasingly popular tool for training deep learning models, namely synthetic data. It is expected that the field of synthetic data will undergo exponential growth in the near future. This book serves as a comprehensive survey of the field. In the simplest case, synthetic data refers to computer-generated graphics used to train computer vision models. There are many more facets of synthetic data to consider. In the section on basic computer vision, the book discusses fundamental computer vision problems, both low-level (e.g., optical flow estimation) and high-level (e.g., object detection and semantic segmentation), synthetic environments and datasets for outdoor and urban scenes (autonomous driving), indoor scenes (indoor navigation), aerial navigation, and simulation environments for robotics. Additionally, it touches upon applications of synthetic data outside computer vision (in neural programming, bioinformatics, NLP, and more). It also surveys the work on improving synthetic data development and alternative ways to produce it such as GANs. The book introduces and reviews several different approaches to synthetic data in various domains of machine learning, most notably the following fields: domain adaptation for making synthetic data more realistic and/or adapting the models to be trained on synthetic data and differential privacy for generating synthetic data with privacy guarantees. This discussion is accompanied by an introduction into generative adversarial networks (GAN) and an introduction to differential privacy.

50 years of Statistical Physics in Mexico: Development, State of the Art and Perspectives

Author : Ramon Castañeda-Priego
Publisher : Frontiers Media SA
ISBN 13 : 2889712958
Total Pages : 213 pages
Book Rating : 4.8/5 (897 download)

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Book Synopsis 50 years of Statistical Physics in Mexico: Development, State of the Art and Perspectives by : Ramon Castañeda-Priego

Download or read book 50 years of Statistical Physics in Mexico: Development, State of the Art and Perspectives written by Ramon Castañeda-Priego and published by Frontiers Media SA. This book was released on 2021-09-13 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt:

A Guided Tour of Artificial Intelligence Research

Author : Pierre Marquis
Publisher : Springer Nature
ISBN 13 : 3030061701
Total Pages : 584 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis A Guided Tour of Artificial Intelligence Research by : Pierre Marquis

Download or read book A Guided Tour of Artificial Intelligence Research written by Pierre Marquis and published by Springer Nature. This book was released on 2020-05-08 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI. The book is split into three volumes: - the first volume brings together twenty-three chapters dealing with the foundations of knowledge representation and the formalization of reasoning and learning (Volume 1. Knowledge representation, reasoning and learning) - the second volume offers a view of AI, in fourteen chapters, from the side of the algorithms (Volume 2. AI Algorithms) - the third volume, composed of sixteen chapters, describes the main interfaces and applications of AI (Volume 3. Interfaces and applications of AI). This third volume is dedicated to the interfaces of AI with various fields, with which strong links exist either at the methodological or at the applicative levels. The foreword of this volume reminds us that AI was born for a large part from cybernetics. Chapters are devoted to disciplines that are historically sisters of AI: natural language processing, pattern recognition and computer vision, and robotics. Also close and complementary to AI due to their direct links with information are databases, the semantic web, information retrieval and human-computer interaction. All these disciplines are privileged places for applications of AI methods. This is also the case for bioinformatics, biological modeling and computational neurosciences. The developments of AI have also led to a dialogue with theoretical computer science in particular regarding computability and complexity. Besides, AI research and findings have renewed philosophical and epistemological questions, while their cognitive validity raises questions to psychology. The volume also discusses some of the interactions between science and artistic creation in literature and in music. Lastly, an epilogue concludes the three volumes of this Guided Tour of AI Research by providing an overview of what has been achieved by AI, emphasizing AI as a science, and not just as an innovative technology, and trying to dispel some misunderstandings.

Network Bioscience, 2nd Edition

Author : Marco Pellegrini
Publisher : Frontiers Media SA
ISBN 13 : 288963650X
Total Pages : 270 pages
Book Rating : 4.8/5 (896 download)

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Book Synopsis Network Bioscience, 2nd Edition by : Marco Pellegrini

Download or read book Network Bioscience, 2nd Edition written by Marco Pellegrini and published by Frontiers Media SA. This book was released on 2020-03-27 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Network science has accelerated a deep and successful trend in research that influences a range of disciplines like mathematics, graph theory, physics, statistics, data science and computer science (just to name a few) and adapts the relevant techniques and insights to address relevant but disparate social, biological, technological questions. We are now in an era of 'big biological data' supported by cost-effective high-throughput genomic, transcriptomic, proteomic, metabolomic data collection techniques that allow one to take snapshots of the cells' molecular profiles in a systematic fashion. Moreover recently, also phenotypic data, data on diseases, symptoms, patients, etc. are being collected at nation-wide level thus giving us another source of highly related (causal) 'big data'. This wealth of data is usually modeled as networks (aka binary relations, graphs or webs) of interactions, (including protein-protein, metabolic, signaling and transcription-regulatory interactions). The network model is a key view point leading to the uncovering of mesoscale phenomena, thus providing an essential bridge between the observable phenotypes and 'omics' underlying mechanisms. Moreover, network analysis is a powerful 'hypothesis generation' tool guiding the scientific cycle of 'data gathering', 'data interpretation, 'hypothesis generation' and 'hypothesis testing'. A major challenge in contemporary research is the synthesis of deep insights coming from network science with the wealth of data (often noisy, contradictory, incomplete and difficult to replicate) so to answer meaningful biological questions, in a quantifiable way using static and dynamic properties of biological networks.

Machine Learning Meets Quantum Physics

Author : Kristof T. Schütt
Publisher : Springer Nature
ISBN 13 : 3030402452
Total Pages : 473 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Machine Learning Meets Quantum Physics by : Kristof T. Schütt

Download or read book Machine Learning Meets Quantum Physics written by Kristof T. Schütt and published by Springer Nature. This book was released on 2020-06-03 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designing molecules and materials with desired properties is an important prerequisite for advancing technology in our modern societies. This requires both the ability to calculate accurate microscopic properties, such as energies, forces and electrostatic multipoles of specific configurations, as well as efficient sampling of potential energy surfaces to obtain corresponding macroscopic properties. Tools that can provide this are accurate first-principles calculations rooted in quantum mechanics, and statistical mechanics, respectively. Unfortunately, they come at a high computational cost that prohibits calculations for large systems and long time-scales, thus presenting a severe bottleneck both for searching the vast chemical compound space and the stupendously many dynamical configurations that a molecule can assume. To overcome this challenge, recently there have been increased efforts to accelerate quantum simulations with machine learning (ML). This emerging interdisciplinary community encompasses chemists, material scientists, physicists, mathematicians and computer scientists, joining forces to contribute to the exciting hot topic of progressing machine learning and AI for molecules and materials. The book that has emerged from a series of workshops provides a snapshot of this rapidly developing field. It contains tutorial material explaining the relevant foundations needed in chemistry, physics as well as machine learning to give an easy starting point for interested readers. In addition, a number of research papers defining the current state-of-the-art are included. The book has five parts (Fundamentals, Incorporating Prior Knowledge, Deep Learning of Atomistic Representations, Atomistic Simulations and Discovery and Design), each prefaced by editorial commentary that puts the respective parts into a broader scientific context.

Acm-Bcb'17

Author : Nurit Haspel
Publisher :
ISBN 13 : 9781450347228
Total Pages : pages
Book Rating : 4.3/5 (472 download)

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Book Synopsis Acm-Bcb'17 by : Nurit Haspel

Download or read book Acm-Bcb'17 written by Nurit Haspel and published by . This book was released on 2017-08-20 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: BCB '17: ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics Aug 20, 2017-Aug 23, 2017 Boston, USA. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.

Artificial Intelligence in Anesthesiology

Author : Ming Xia
Publisher : Springer Nature
ISBN 13 : 981995925X
Total Pages : 114 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Artificial Intelligence in Anesthesiology by : Ming Xia

Download or read book Artificial Intelligence in Anesthesiology written by Ming Xia and published by Springer Nature. This book was released on 2023-11-23 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: Considering the rapid developments in digital and information technologies, artificial intelligence has long been a hot topic in medicine. This book discusses applications of artificial intelligence in anaesthesiology, including control of anesthesia, risk prediction, ultrasound guidance, pain management, and operating room logistics. This book first defines basic concepts of AI, and give a brief overview of a few algorithms frequently used in AI and machine learning. A review of current AI and machine learning applications for the prediction of anesthesia conditions is also discussed, including those for the prediction of difficult airways before surgery, of adverse events and sedation effects during surgery, and of vomiting and pain after surgery. Even without extensive promotion and clinical application, AI is in development in anesthesiology; furthermore, it has a great deal of potential to maintain further development in the future. Lastly, ethical and safety considerations are discussed alongside AI limitations and challenges in anesthesiology.

Big Data Analytics for Healthcare

Author : Pantea Keikhosrokiani
Publisher : Academic Press
ISBN 13 : 0323985165
Total Pages : 356 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Big Data Analytics for Healthcare by : Pantea Keikhosrokiani

Download or read book Big Data Analytics for Healthcare written by Pantea Keikhosrokiani and published by Academic Press. This book was released on 2022-05-19 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics and Medical Information Systems presents the valuable use of artificial intelligence and big data analytics in healthcare and medical sciences. It focuses on theories, methods and approaches in which data analytic techniques can be used to examine medical data to provide a meaningful pattern for classification, diagnosis, treatment, and prediction of diseases. The book discusses topics such as theories and concepts of the field, and how big medical data mining techniques and applications can be applied to classification, diagnosis, treatment, and prediction of diseases. In addition, it covers social, behavioral, and medical fake news analytics to prevent medical misinformation and myths. It is a valuable resource for graduate students, researchers and members of biomedical field who are interested in learning more about analytic tools to support their work. - Presents theories, methods and approaches in which data analytic techniques are used for medical data - Brings practical information on how to use big data for classification, diagnosis, treatment, and prediction of diseases - Discusses social, behavioral, and medical fake news analytics for medical information systems

ACM-BCB'17

Author :
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (12 download)

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Book Synopsis ACM-BCB'17 by :

Download or read book ACM-BCB'17 written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Integrative Genomics and Network Biology in Livestock and other Domestic Animals

Author : David E. MacHugh
Publisher : Frontiers Media SA
ISBN 13 : 2889639991
Total Pages : 450 pages
Book Rating : 4.8/5 (896 download)

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Book Synopsis Integrative Genomics and Network Biology in Livestock and other Domestic Animals by : David E. MacHugh

Download or read book Integrative Genomics and Network Biology in Livestock and other Domestic Animals written by David E. MacHugh and published by Frontiers Media SA. This book was released on 2020-09-11 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.

Biocomputing 2019 - Proceedings Of The Pacific Symposium

Author : Russ B Altman
Publisher : World Scientific
ISBN 13 : 9813279834
Total Pages : 472 pages
Book Rating : 4.8/5 (132 download)

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Book Synopsis Biocomputing 2019 - Proceedings Of The Pacific Symposium by : Russ B Altman

Download or read book Biocomputing 2019 - Proceedings Of The Pacific Symposium written by Russ B Altman and published by World Scientific. This book was released on 2018-11-28 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Pacific Symposium on Biocomputing (PSB) 2019 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2019 will be held on January 3 - 7, 2019 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference.PSB 2019 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's 'hot topics.' In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field.