Differentiation Between Resting State Fmri Data From Adhd And Normal Subjects Based On Functional Connectivity And Machine Learning
Download Differentiation Between Resting State Fmri Data From Adhd And Normal Subjects Based On Functional Connectivity And Machine Learning full books in PDF, epub, and Kindle. Read online free Differentiation Between Resting State Fmri Data From Adhd And Normal Subjects Based On Functional Connectivity And Machine Learning ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : Malek Mouhoub |
| Publisher | : Springer |
| Total Pages | : 432 |
| Release | : 2017-05-06 |
| Genre | : Computers |
| ISBN | : 3319573519 |
This book constitutes the refereed proceedings of the 30th Canadian Conference on Artificial Intelligence, Canadian AI 2017, held in Edmonton, AB, Canada, in May 2017. The 19 regular papers and 24 short papers presented together with 6 Graduate Student Symposium papers were carefully reviewed and selected from 62 submissions. The focus of the conference was on the following subjects: Data Mining and Machine Learning; Planning and Combinatorial Optimization; AI Applications; Natural Language Processing; Uncertainty and Preference Reasoning; and Agent Systems.
| Author | : Renu Vyas |
| Publisher | : Springer Nature |
| Total Pages | : 229 |
| Release | : 2020-05-11 |
| Genre | : Medical |
| ISBN | : 9811520631 |
This book provides a single source of information on three major bioengineering areas: engineering at the cellular and molecular level; biomedical devices / instrument engineering; and data engineering. It explores the latest strategies that are essential to advancing our understanding of the mechanisms of human diseases, the development of new enzyme-based technologies, diagnostics, prosthetics, high-performance computing platforms for managing huge amounts of biological data, and the use of deep learning methods to create predictive models. The book also highlights the growing importance of integrating chemistry into life sciences research, most notably concerning the development and evaluation of nanomaterials and nanoparticles and their interactions with biological material. The underlying interdisciplinary theme of bioengineering is addressed in a range of multifaceted applications and worked out examples provided in each chapter.
| Author | : |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 1987 |
| Genre | : |
| ISBN | : |
| Author | : Satyabrata Roy |
| Publisher | : Springer Nature |
| Total Pages | : 764 |
| Release | : 2023-11-13 |
| Genre | : Technology & Engineering |
| ISBN | : 9819926025 |
This book presents high-quality, peer-reviewed papers from the International Conference on “Innovations in Computational Intelligence and Computer Vision (ICICV 2022),” hosted by Manipal University Jaipur, Rajasthan, India, on 24–25 November 2022. The book includes a collection of innovative ideas from researchers, scientists, academics, industry professionals and students. The book covers a variety of topics, such as artificial intelligence and computer vision, image processing and video analysis, applications and services of artificial intelligence and computer vision, interdisciplinary areas combining artificial intelligence and computer vision, and other innovative practices.
| Author | : Ervin Sejdic |
| Publisher | : CRC Press |
| Total Pages | : 624 |
| Release | : 2018-07-04 |
| Genre | : Medical |
| ISBN | : 149877346X |
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.
| Author | : Rajesh K. Kana |
| Publisher | : Frontiers E-books |
| Total Pages | : 265 |
| Release | : 2014-09-23 |
| Genre | : Autism |
| ISBN | : 2889192822 |
The brain's ability to process information crucially relies on connectivity. Understanding how the brain processes complex information and how such abilities are disrupted in individuals with neuropsychological disorders will require an improved understanding of brain connectivity. Autism is an intriguingly complex neurodevelopmental disorder with multidimensional symptoms and cognitive characteristics. A biological origin for autism spectrum disorders (ASD) had been proposed even in the earliest published accounts (Kanner, 1943; Asperger, 1944). Despite decades of research, a focal neurobiological marker for autism has been elusive. Nevertheless, disruptions in interregional and functional and anatomical connectivity have been a hallmark of neural functioning in ASD. Theoretical accounts of connectivity perceive ASD as a cognitive and neurobiological disorder associated with altered functioning of integrative circuitry. Neuroimaging studies have reported disruptions in functional connectivity (synchronization of activated brain areas) during cognitive tasks and during task-free resting states. While these insights are valuable, they do not address the time-lagged causality and directionality of such correlations. Despite the general promise of the connectivity account of ASD, inconsistencies and methodological differences among studies call for more thorough investigations. A comprehensive neurological account of ASD should incorporate functional, effective, and anatomical connectivity measures and test the diagnostic utility of such measures. In addition, questions pertaining to how cognitive and behavioral intervention can target connection abnormalities in ASD should be addressed. This research topic of the Frontiers in Human Neuroscience addresses “Brain Connectivity in Autism” primarily from cognitive neuroscience and neuroimaging perspectives.
| Author | : Yuhui Du |
| Publisher | : Frontiers Media SA |
| Total Pages | : 288 |
| Release | : 2020-07-10 |
| Genre | : |
| ISBN | : 2889634043 |
There has been increasing interests in exploring biomarkers from brain images, aiming to have a better understanding and a more effective diagnosis of brain disorders such as schizophrenia, bipolar disorder, schizoaffective disorder, autism spectrum disorder, attention-deficit/hyperactivity disorder, Alzheimer’s disease and so on. Therefore, it is important to identify disease-specific changes for distinguishing healthy controls and patients with brain disorders as well as for differentiating patients with different disorders showing similar clinical symptoms. Biomarkers can be identified from different types of brain Imaging techniques including functional magnetic resonance imaging (fMRI), structural MRI, positron emission tomography (PET), electroencephalography (EEG), and magnetoencephalography (MEG) by using statistical analysis methods. Furthermore, based on measures from brain imaging techniques, machine learning techniques can help to classify or predict disease for individual subjects. In fact, fusion of features from multiple modalities may benefit the understanding of disease mechanism and improve the classification performance. This Research Topic further explores the functional or structural alterations in brain disorders.
| Author | : Junghun Cho |
| Publisher | : Frontiers Media SA |
| Total Pages | : 222 |
| Release | : 2023-09-07 |
| Genre | : Science |
| ISBN | : 2832533329 |
| Author | : Donald W. Pfaff |
| Publisher | : Springer |
| Total Pages | : 0 |
| Release | : 2016-10-27 |
| Genre | : Medical |
| ISBN | : 9781493934737 |
Edited and authored by a wealth of international experts in neuroscience and related disciplines, this key new resource aims to offer medical students and graduate researchers around the world a comprehensive introduction and overview of modern neuroscience. Neuroscience research is certain to prove a vital element in combating mental illness in its various incarnations, a strategic battleground in the future of medicine, as the prevalence of mental disorders is becoming better understood each year. Hundreds of millions of people worldwide are affected by mental, behavioral, neurological and substance use disorders. The World Health Organization estimated in 2002 that 154 million people globally suffer from depression and 25 million people from schizophrenia; 91 million people are affected by alcohol use disorders and 15 million by drug use disorders. A more recent WHO report shows that 50 million people suffer from epilepsy and 24 million from Alzheimer’s and other dementias. Because neuroscience takes the etiology of disease—the complex interplay between biological, psychological, and sociocultural factors—as its object of inquiry, it is increasingly valuable in understanding an array of medical conditions. A recent report by the United States’ Surgeon General cites several such diseases: schizophrenia, bipolar disorder, early-onset depression, autism, attention deficit/ hyperactivity disorder, anorexia nervosa, and panic disorder, among many others. Not only is this volume a boon to those wishing to understand the future of neuroscience, it also aims to encourage the initiation of neuroscience programs in developing countries, featuring as it does an appendix full of advice on how to develop such programs. With broad coverage of both basic science and clinical issues, comprising around 150 chapters from a diversity of international authors and including complementary video components, Neuroscience in the 21st Century in its second edition serves as a comprehensive resource to students and researchers alike.
| Author | : Tomiki Sumiyoshi |
| Publisher | : Frontiers Media SA |
| Total Pages | : 261 |
| Release | : 2019-11-25 |
| Genre | : |
| ISBN | : 2889630552 |
Disturbances of various domains of cognitive function have been shown to provide a major determinant of outcome for patients with psychiatric conditions. Cognitive impairment is present in an array of diseases, including schizophrenia (with its prodromal stage), mood disorder, autism spectrum disorder, obsessive-compulsive disorder, anxiety disorder, post-traumatic disorder, and eating disorder. In an effort to develop effective therapeutics for cognitive impairment, bridging of preclinical and clinical evidence has been attempted. This edited Book will provide a forum for researchers and clinicians interested in the phenomenology, underlying mechanisms, and treatment of cognitive impairment associated with psychiatric illnesses. Twenty-eight contributions from 8 countries in Europe, Middle East, Asia, North America, and South America represent studies dealing with genetic, molecular, imaging, physiological, psychological, and behavioral issues. Information in this Book will facilitate the development of therapeutics of greater clinical value.
