Recent Advances And Challenges On Big Data Analysis In Neuroimaging
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Recent Advances And Challenges On Big Data Analysis In Neuroimaging
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Author : Jian Kang
language : en
Publisher: Frontiers Media SA
Release Date : 2017-05-17
Recent Advances And Challenges On Big Data Analysis In Neuroimaging written by Jian Kang and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-17 with categories.
Big data is revolutionizing our ability to measure and study the human brain. New technology increases the resolution of images that are being study as well as enables researchers to study the brain as it functions. These technological advances are combined with efforts to collect neuroimaging data on large numbers of subjects, in some cases longitudinally. This combination of advances in measurement and scope of studies requires novel development in the statistical analysis. Fast, scalable, robust and accurate models and approaches need to be developed to make headway on these problems. This volume represents a unique collection of researchers providing deep insights on the statistical analysis of big neuroimaging data.
Recent Advances And Challenges In The Treatment Of Major Depressive Disorder
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Author : Yong-Ku Kim
language : en
Publisher: Springer Nature
Release Date : 2024-09-12
Recent Advances And Challenges In The Treatment Of Major Depressive Disorder written by Yong-Ku Kim and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-12 with Science categories.
This book reviews all aspects of major depressive disorder (MDD), casting light on its neurobiological underpinnings and describing the most recent advances in management. The book is divided into four sections, the first of which discusses MDD from a network science perspective, highlighting the alterations in functional and structural connectivity and presenting insights achieved through resting state functional MRI and the development of neuroimaging-based biomarkers. The second section examines important diagnostic and neurobiological issues, while the third considers the currently available specific treatments for MDD, including biofeedback, neurofeedback, cognitive behavioral therapy, acceptance and commitment therapy, neuromodulation therapy, psychodynamic therapy, and complementary and alternative medicine. A concluding section is devoted to promising emerging treatments, from novel psychopharmacological therapies through to virtual reality treatment, immunotherapy, biomarker-guided tailored therapy, and more. Written by leading experts from across the world, the book will be an excellent source of information for both researchers and practitioners.
Handbook Of Data Science Approaches For Biomedical Engineering
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Author : Valentina Emilia Balas
language : en
Publisher: Academic Press
Release Date : 2019-11-13
Handbook Of Data Science Approaches For Biomedical Engineering written by Valentina Emilia Balas and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-13 with Science categories.
Handbook of Data Science Approaches for Biomedical Engineering covers the research issues and concepts of biomedical engineering progress and the ways they are aligning with the latest technologies in IoT and big data. In addition, the book includes various real-time/offline medical applications that directly or indirectly rely on medical and information technology. Case studies in the field of medical science, i.e., biomedical engineering, computer science, information security, and interdisciplinary tools, along with modern tools and the technologies used are also included to enhance understanding. Today, the role of Big Data and IoT proves that ninety percent of data currently available has been generated in the last couple of years, with rapid increases happening every day. The reason for this growth is increasing in communication through electronic devices, sensors, web logs, global positioning system (GPS) data, mobile data, IoT, etc. - Provides in-depth information about Biomedical Engineering with Big Data and Internet of Things - Includes technical approaches for solving real-time healthcare problems and practical solutions through case studies in Big Data and Internet of Things - Discusses big data applications for healthcare management, such as predictive analytics and forecasting, big data integration for medical data, algorithms and techniques to speed up the analysis of big medical data, and more
Recent Advances And The Future Generation Of Neuroinformatics Infrastructure
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Author : Xi Cheng
language : en
Publisher: Frontiers Media SA
Release Date : 2015-12-11
Recent Advances And The Future Generation Of Neuroinformatics Infrastructure written by Xi Cheng and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-11 with Neurosciences. Biological psychiatry. Neuropsychiatry categories.
The huge volume of multi-modal neuroimaging data across different neuroscience communities has posed a daunting challenge to traditional methods of data sharing, data archiving, data processing and data analysis. Neuroinformatics plays a crucial role in creating advanced methodologies and tools for the handling of varied and heterogeneous datasets in order to better understand the structure and function of the brain. These tools and methodologies not only enhance data collection, analysis, integration, interpretation, modeling, and dissemination of data, but also promote data sharing and collaboration. This Neuroinformatics Research Topic aims to summarize the state-of-art of the current achievements and explores the directions for the future generation of neuroinformatics infrastructure. The publications present solutions for data archiving, data processing and workflow, data mining, and system integration methodologies. Some of the systems presented are large in scale, geographically distributed, and already have a well-established user community. Some discuss opportunities and methodologies that facilitate large-scale parallel data processing tasks under a heterogeneous computational environment. We wish to stimulate on-going discussions at the level of the neuroinformatics infrastructure including the common challenges, new technologies of maximum benefit, key features of next generation infrastructure, etc. We have asked leading research groups from different research areas of neuroscience/neuroimaging to provide their thoughts on the development of a state of the art and highly-efficient neuroinformatics infrastructure. Such discussions will inspire and help guide the development of a state of the art, highly-efficient neuroinformatics infrastructure.
Collaborative Efforts For Understanding The Human Brain
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Author : Sook-Lei Liew
language : en
Publisher: Frontiers Media SA
Release Date : 2019-10-10
Collaborative Efforts For Understanding The Human Brain written by Sook-Lei Liew and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-10 with categories.
The human brain is incredibly complex, and the more we learn about it, the more we realize how much we need a truly interdisciplinary team to make sense of its intricacies. This eBook presents the latest efforts in collaborative team science from around the world, all aimed at understanding the human brain.
Big Data In Psychiatry And Neurology
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Author : Ahmed Moustafa
language : en
Publisher: Academic Press
Release Date : 2021-06-11
Big Data In Psychiatry And Neurology written by Ahmed Moustafa and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-11 with Medical categories.
Big Data in Psychiatry and Neurology provides an up-to-date overview of achievements in the field of big data in Psychiatry and Medicine, including applications of big data methods to aging disorders (e.g., Alzheimer's disease and Parkinson's disease), mood disorders (e.g., major depressive disorder), and drug addiction. This book will help researchers, students and clinicians implement new methods for collecting big datasets from various patient populations. Further, it will demonstrate how to use several algorithms and machine learning methods to analyze big datasets, thus providing individualized treatment for psychiatric and neurological patients. As big data analytics is gaining traction in psychiatric research, it is an essential component in providing predictive models for both clinical practice and public health systems. As compared with traditional statistical methods that provide primarily average group-level results, big data analytics allows predictions and stratification of clinical outcomes at an individual subject level. - Discusses longitudinal big data and risk factors surrounding the development of psychiatric disorders - Analyzes methods in using big data to treat psychiatric and neurological disorders - Describes the role machine learning can play in the analysis of big data - Demonstrates the various methods of gathering big data in medicine - Reviews how to apply big data to genetics
Engineering And Technology Management In Challenging Times
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Author : Ferhan Çebi
language : en
Publisher: Springer Nature
Release Date : 2024-11-29
Engineering And Technology Management In Challenging Times written by Ferhan Çebi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-29 with Computers categories.
The book is an important resource to effectively combat these challenges and guide businesses and institutions toward success. Today's world is experiencing a period in which, on the one hand, technical advances, innovations, and changes are developing at an increasingly rapid pace, and on the other hand, uncertain global challenges are emerging. Managers in the field of engineering and technology must skillfully manage this complexity and uncertainty. Reasons to Consider Reading This Book: · Acquiring advanced methodologies and tools to efficiently oversee engineering and technology projects, especially in highly volatile circumstances. · Gaining valuable insights from industry experts and experienced professionals as they impart their knowledge, expertise, and groundbreaking ideas. · Experiencing practical approaches for learning effective strategies and tangible techniques to improve productivity, maximize resources, and promote creativity. The book helps · Engineers and technologists to be able to find solutions to the problems they encounter with the most up-to-date methods. · Business leaders to be able to have a deep understanding of how to effectively leverage technology to achieve strategic advantage and ensure the resilience of their companies · Students and educators to be able to acquire new knowledge by combining academic knowledge with practical application This book serves as a comprehensive guide that provides a clear path to adaptability, creativity, and achievement in an uncertain global landscape. The book emphasizes “Do not merely endure the difficulties and solve them; improve, shape, and take charge with assurance”.
Leveraging Biomedical And Healthcare Data
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Author : Firas Kobeissy
language : en
Publisher: Academic Press
Release Date : 2018-11-23
Leveraging Biomedical And Healthcare Data written by Firas Kobeissy and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-23 with Medical categories.
Leveraging Biomedical and Healthcare Data: Semantics, Analytics and Knowledge provides an overview of the approaches used in semantic systems biology, introduces novel areas of its application, and describes step-wise protocols for transforming heterogeneous data into useful knowledge that can influence healthcare and biomedical research. Given the astronomical increase in the number of published reports, papers, and datasets over the last few decades, the ability to curate this data has become a new field of biomedical and healthcare research. This book discusses big data text-based mining to better understand the molecular architecture of diseases and to guide health care decision. It will be a valuable resource for bioinformaticians and members of several areas of the biomedical field who are interested in understanding more about how to process and apply great amounts of data to improve their research. Includes at each section resource pages containing a list of available curated raw and processed data that can be used by researchers in the field Provides demonstrative and relevant examples that serve as a general tutorial Presents a list of algorithm names and computational tools available for basic and clinical researchers
Signal Processing And Machine Learning For Biomedical Big Data
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Author : Ervin Sejdic
language : en
Publisher: CRC Press
Release Date : 2018-07-04
Signal Processing And Machine Learning For Biomedical Big Data written by Ervin Sejdic and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-04 with Medical categories.
Within the healthcare domain, big data is defined as any ``high volume, high diversity biological, clinical, environmental, and lifestyle information collected from single individuals to large cohorts, in relation to their health and wellness status, at one or several time points.'' Such data is crucial because within it lies vast amounts of invaluable information that could potentially change a patient's life, opening doors to alternate therapies, drugs, and diagnostic tools. Signal Processing and Machine Learning for Biomedical Big Data thus discusses modalities; the numerous ways in which this data is captured via sensors; and various sample rates and dimensionalities. Capturing, analyzing, storing, and visualizing such massive data has required new shifts in signal processing paradigms and new ways of combining signal processing with machine learning tools. This book covers several of these aspects in two ways: firstly, through theoretical signal processing chapters where tools aimed at big data (be it biomedical or otherwise) are described; and, secondly, through application-driven chapters focusing on existing applications of signal processing and machine learning for big biomedical data. This text aimed at the curious researcher working in the field, as well as undergraduate and graduate students eager to learn how signal processing can help with big data analysis. It is the hope of Drs. Sejdic and Falk that this book will bring together signal processing and machine learning researchers to unlock existing bottlenecks within the healthcare field, thereby improving patient quality-of-life. Provides an overview of recent state-of-the-art signal processing and machine learning algorithms for biomedical big data, including applications in the neuroimaging, cardiac, retinal, genomic, sleep, patient outcome prediction, critical care, and rehabilitation domains. Provides contributed chapters from world leaders in the fields of big data and signal processing, covering topics such as data quality, data compression, statistical and graph signal processing techniques, and deep learning and their applications within the biomedical sphere. This book’s material covers how expert domain knowledge can be used to advance signal processing and machine learning for biomedical big data applications.
Brain Computer Interface
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Author : M. G. Sumithra
language : en
Publisher: John Wiley & Sons
Release Date : 2023-03-14
Brain Computer Interface written by M. G. Sumithra and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-14 with Computers categories.
BRAIN-COMPUTER INTERFACE It covers all the research prospects and recent advancements in the brain-computer interface using deep learning. The brain-computer interface (BCI) is an emerging technology that is developing to be more functional in practice. The aim is to establish, through experiences with electronic devices, a communication channel bridging the human neural networks within the brain to the external world. For example, creating communication or control applications for locked-in patients who have no control over their bodies will be one such use. Recently, from communication to marketing, recovery, care, mental state monitoring, and entertainment, the possible application areas have been expanding. Machine learning algorithms have advanced BCI technology in the last few decades, and in the sense of classification accuracy, performance standards have been greatly improved. For BCI to be effective in the real world, however, some problems remain to be solved. Research focusing on deep learning is anticipated to bring solutions in this regard. Deep learning has been applied in various fields such as computer vision and natural language processing, along with BCI growth, outperforming conventional approaches to machine learning. As a result, a significant number of researchers have shown interest in deep learning in engineering, technology, and other industries; convolutional neural network (CNN), recurrent neural network (RNN), and generative adversarial network (GAN). Audience Researchers and industrialists working in brain-computer interface, deep learning, machine learning, medical image processing, data scientists and analysts, machine learning engineers, electrical engineering, and information technologists.