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Author: Athanasios Alexiou Publisher: Frontiers Media SA ISBN: 2889631281 Category : Languages : en Pages : 501
Book Description
Alzheimer’s disease is undoubtedly the major health challenge of our Century with significant social and economic consequences. This Frontiers eBook offers a contribution of 39 innovative papers on the multidimensional and crucial problem of Alzheimer’s disease management and treatment. Several perspectives, research updates, and trials describing methods on potential diagnosis and treatment are presented including biological mechanisms, biomarkers and risk factors for an early and efficient prognosis, diagnosis and prevention. Additionally, while the rapidly increasing Alzheimer’s disease population demands holistic solutions and clinical studies with new therapeutic target approaches, several of the contributive papers present promising drugs targeting Alzheimer’s disease treatment. We give our deepest acknowledgment to all the authors for their important and innovative contributions, to the reviewers for their valuable recommendations on improving the submitting studies and all the Frontiers Editorial team for continuous support.
Author: Athanasios Alexiou Publisher: Frontiers Media SA ISBN: 2889631281 Category : Languages : en Pages : 501
Book Description
Alzheimer’s disease is undoubtedly the major health challenge of our Century with significant social and economic consequences. This Frontiers eBook offers a contribution of 39 innovative papers on the multidimensional and crucial problem of Alzheimer’s disease management and treatment. Several perspectives, research updates, and trials describing methods on potential diagnosis and treatment are presented including biological mechanisms, biomarkers and risk factors for an early and efficient prognosis, diagnosis and prevention. Additionally, while the rapidly increasing Alzheimer’s disease population demands holistic solutions and clinical studies with new therapeutic target approaches, several of the contributive papers present promising drugs targeting Alzheimer’s disease treatment. We give our deepest acknowledgment to all the authors for their important and innovative contributions, to the reviewers for their valuable recommendations on improving the submitting studies and all the Frontiers Editorial team for continuous support.
Author: Atsushi Kawaguchi Publisher: CRC Press ISBN: 1000369870 Category : Mathematics Languages : en Pages : 214
Book Description
This book describes methods for statistical brain imaging data analysis from both the perspective of methodology and from the standpoint of application for software implementation in neuroscience research. These include those both commonly used (traditional established) and state of the art methods. The former is easier to do due to the availability of appropriate software. To understand the methods it is necessary to have some mathematical knowledge which is explained in the book with the help of figures and descriptions of the theory behind the software. In addition, the book includes numerical examples to guide readers on the working of existing popular software. The use of mathematics is reduced and simplified for non-experts using established methods, which also helps in avoiding mistakes in application and interpretation. Finally, the book enables the reader to understand and conceptualize the overall flow of brain imaging data analysis, particularly for statisticians and data-scientists unfamiliar with this area. The state of the art method described in the book has a multivariate approach developed by the authors’ team. Since brain imaging data, generally, has a highly correlated and complex structure with large amounts of data, categorized into big data, the multivariate approach can be used as dimension reduction by following the application of statistical methods. The R package for most of the methods described is provided in the book. Understanding the background theory is helpful in implementing the software for original and creative applications and for an unbiased interpretation of the output. The book also explains new methods in a conceptual manner. These methodologies and packages are commonly applied in life science data analysis. Advanced methods to obtain novel insights are introduced, thereby encouraging the development of new methods and applications for research into medicine as a neuroscience.
Author: Valerio Rizzo Publisher: Frontiers Media SA ISBN: 2889662993 Category : Science Languages : en Pages : 180
Book Description
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.
Author: Andrea Mechelli Publisher: Academic Press ISBN: 0128157402 Category : Medical Languages : en Pages : 412
Book Description
Machine Learning is an area of artificial intelligence involving the development of algorithms to discover trends and patterns in existing data; this information can then be used to make predictions on new data. A growing number of researchers and clinicians are using machine learning methods to develop and validate tools for assisting the diagnosis and treatment of patients with brain disorders. Machine Learning: Methods and Applications to Brain Disorders provides an up-to-date overview of how these methods can be applied to brain disorders, including both psychiatric and neurological disease. This book is written for a non-technical audience, such as neuroscientists, psychologists, psychiatrists, neurologists and health care practitioners. - Provides a non-technical introduction to machine learning and applications to brain disorders - Includes a detailed description of the most commonly used machine learning algorithms as well as some novel and promising approaches - Covers the main methodological challenges in the application of machine learning to brain disorders - Provides a step-by-step tutorial for implementing a machine learning pipeline to neuroimaging data in Python
Author: Manish Kumar Gupta Publisher: Elsevier ISBN: 0443160937 Category : Science Languages : en Pages : 434
Book Description
Integrative Omics: Concepts, Methodology and Applications provides a holistic and integrated view of defining and applying network approaches, integrative tools, and methods to solve problems for the rationalization of genotype to phenotype relationships. The reference includes a range of chapters in a systemic 'step by step' manner, which begins with the basic concepts from Omic to Multi Integrative Omics approaches, followed by their full range of approaches, applications, emerging trends, and future trends. All key areas of Omics are covered including biological databases, sequence alignment, pharmacogenomics, nutrigenomics and microbial omics, integrated omics for Food Science and Identification of genes associated with disease, clinical data integration and data warehousing, translational omics as well as omics technology policy and society research. Integrative Omics: Concepts, Methodology and Applications highlights the recent concepts, methodologies, advancements in technologies and is also well-suited for researchers from both academic and industry background, undergraduate and graduate students who are mainly working in the area of computational systems biology, integrative omics and translational science. The book bridges the gap between biological sciences, physical sciences, computer science, statistics, data science, information technology and mathematics by presenting content specifically dedicated to mathematical models of biological systems. - Provides a holistic, integrated view of a defining and applying network approach, integrative tools, and methods to solve problems for rationalization of genotype to phenotype relationships - Offers an interdisciplinary approach to Databases, data analytics techniques, biological tools, network construction, analysis, modeling, prediction and simulation of biological systems leading to 'translational research', i.e., drug discovery, drug target prediction, and precision medicine - Covers worldwide methods, concepts, databases, and tools used in the construction of integrated pathways
Author: Xiaoying Tang Publisher: Frontiers Media SA ISBN: 2889459845 Category : Languages : en Pages : 118
Book Description
Computational Anatomy (CA) is an emerging discipline aiming to understand anatomy by utilizing a comprehensive set of mathematical tools. CA focuses on providing precise statistical encodings of anatomy with direct application to a broad range of biological and medical settings. During the past two decades, there has been an ever-increasing pace in the development of neuroimaging techniques, delivering in vivo information on the anatomy and physiological signals of different human organs through a variety of imaging modalities such as MRI, x-ray, CT, and PET. These multi-modality medical images provide valuable data for accurate interpretation and estimation of various biological parameters such as anatomical labels, disease types, cognitive states, functional connectivity between distinct anatomical regions, as well as activation responses to specific stimuli. In the era of big neuroimaging data, Bayes’ theorem provides a powerful tool to deliver statistical conclusions by combining the current information and prior experience. When sufficiently good data is available, Bayes’ theorem can utilize it fully and provide statistical inferences/estimations with the least error rate. Bayes’ theorem arose roughly three hundred years ago and has seen extensive application in many fields of science and technology, including recent neuroimaging, ever since. The last fifteen years have seen a great deal of success in the application of Bayes’ theorem to the field of CA and neuroimaging. That said, given that the power and success of Bayes’ rule largely depends on the validity of its probabilistic inputs, it is still a challenge to perform Bayesian estimation and inference on the typically noisy neuroimaging data of the real world. We assembled contributions focusing on recent developments in CA and neuroimaging through Bayesian estimation and inference, in terms of both methodologies and applications. It is anticipated that the articles in this Research Topic will provide a greater insight into the field of Bayesian imaging analysis.
Author: Paul Bracken Publisher: BoD – Books on Demand ISBN: 1838803092 Category : Mathematics Languages : en Pages : 148
Book Description
Differential geometry is a very active field of research and has many applications to areas such as physics, in particular gravity. The chapters in this book cover a number of subjects that will be of interest to workers in these areas. It is hoped that these chapters will be able to provide a useful resource for researchers with regard to current fields of research in this important area.
Author: Shouyi Wang Publisher: Springer ISBN: 3030055876 Category : Computers Languages : en Pages : 509
Book Description
This book constitutes the refereed proceedings of the International Conference on Brain Informatics, BI 2018, held in Arlington, TX, USA, in December 2018. The 46 revised full papers were carefully reviewed and selected from 53 submissions. The papers are grouped thematically on cognitive and computational foundations of brain science, human information processing systems, brain big data analysis, curation and management, informatics paradigms for brain and mental health research, brain-machine intelligence and brain-inspired computing.
Author: Javier Ramírez Publisher: Frontiers Media SA ISBN: 2889662810 Category : Science Languages : en Pages : 127
Book Description
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.
Author: Annalisa Appice Publisher: Springer ISBN: 3319235281 Category : Computers Languages : en Pages : 760
Book Description
The three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. The 131 papers presented in these proceedings were carefully reviewed and selected from a total of 483 submissions. These include 89 research papers, 11 industrial papers, 14 nectar papers, and 17 demo papers. They were organized in topical sections named: classification, regression and supervised learning; clustering and unsupervised learning; data preprocessing; data streams and online learning; deep learning; distance and metric learning; large scale learning and big data; matrix and tensor analysis; pattern and sequence mining; preference learning and label ranking; probabilistic, statistical, and graphical approaches; rich data; and social and graphs. Part III is structured in industrial track, nectar track, and demo track.
Author: Athanasios Alexiou
Author: Athanasios Alexiou
Author: Atsushi Kawaguchi
Author: Valerio Rizzo
Author: Andrea Mechelli
Author: Manish Kumar Gupta
Author: Xiaoying Tang
Author: Paul Bracken
Author: Shouyi Wang
Author: Javier Ramírez
Author: Annalisa Appice