Improving Diagnosis, Treatment, and Prognosis of Neuropsychiatric Disorders by Leveraging Neuroimaging-based Machine Learning PDF Download
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Author: Baojuan Li
Publisher: Frontiers Media SA
ISBN: 2889760960
Category : Science
Languages : en
Pages : 288
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Book Description
Author: Baojuan Li
Publisher: Frontiers Media SA
ISBN: 2889760960
Category : Science
Languages : en
Pages : 288
Get Book Here
Book Description
Author: Bernhard Baune
Publisher: Academic Press
ISBN: 0128131772
Category : Medical
Languages : en
Pages : 594
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Book Description
Personalized Psychiatry presents the first book to explore this novel field of biological psychiatry that covers both basic science research and its translational applications. The book conceptualizes personalized psychiatry and provides state-of-the-art knowledge on biological and neuroscience methodologies, all while integrating clinical phenomenology relevant to personalized psychiatry and discussing important principles and potential models. It is essential reading for advanced students and neuroscience and psychiatry researchers who are investigating the prevention and treatment of mental disorders. - Combines neurobiology with basic science methodologies in genomics, epigenomics and transcriptomics - Demonstrates how the statistical modeling of interacting biological and clinical information could transform the future of psychiatry - Addresses fundamental questions and requirements for personalized psychiatry from a basic research and translational perspective
Author: Neha Sharma
Publisher: John Wiley & Sons
ISBN: 1394270895
Category : Medical
Languages : en
Pages : 328
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Book Description
The book analyzes the combination of intelligent data analytics with the intricacies of biological data that has become a crucial factor for innovation and growth in the fast-changing field of bioinformatics and biomedical systems. Intelligent Data Analytics for Bioinformatics and Biomedical Systems delves into the transformative nature of data analytics for bioinformatics and biomedical research. It offers a thorough examination of advanced techniques, methodologies, and applications that utilize intelligence to improve results in the healthcare sector. With the exponential growth of data in these domains, the book explores how computational intelligence and advanced analytic techniques can be harnessed to extract insights, drive informed decisions, and unlock hidden patterns from vast datasets. From genomic analysis to disease diagnostics and personalized medicine, the book aims to showcase intelligent approaches that enable researchers, clinicians, and data scientists to unravel complex biological processes and make significant strides in understanding human health and diseases. This book is divided into three sections, each focusing on computational intelligence and data sets in biomedical systems. The first section discusses the fundamental concepts of computational intelligence and big data in the context of bioinformatics. This section emphasizes data mining, pattern recognition, and knowledge discovery for bioinformatics applications. The second part talks about computational intelligence and big data in biomedical systems. Based on how these advanced techniques are utilized in the system, this section discusses how personalized medicine and precision healthcare enable treatment based on individual data and genetic profiles. The last section investigates the challenges and future directions of computational intelligence and big data in bioinformatics and biomedical systems. This section concludes with discussions on the potential impact of computational intelligence on addressing global healthcare challenges. Audience Intelligent Data Analytics for Bioinformatics and Biomedical Systems is primarily targeted to professionals and researchers in bioinformatics, genetics, molecular biology, biomedical engineering, and healthcare. The book will also suit academicians, students, and professionals working in pharmaceuticals and interpreting biomedical data.
Author: Ahmed Moustafa
Publisher: Academic Press
ISBN: 0128230029
Category : Medical
Languages : en
Pages : 386
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Book Description
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
Author: Clement Hamani
Publisher: John Wiley & Sons
ISBN: 1118801040
Category : Medical
Languages : en
Pages : 518
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Book Description
Edited by an expert multidisciplinary team, Neuromodulation in Psychiatry is the first reference guide to address both invasive and non-invasive neuromodulation strategies used in psychiatry. Covers basic principles, technical aspects, clinical applications and ethical considerations Presents up-to-date evidence in comprehensive summaries suitable for all levels of experience Each technique is clearly explained along with its implications for real-world clinical practice Allows psychiatrists to make informed decisions regarding neuromodulation for their patients
Author: Raut, Roshani
Publisher: IGI Global
ISBN: 1799875172
Category : Computers
Languages : en
Pages : 304
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Book Description
Deep learning, as a recent AI technique, has proven itself efficient in solving many real-world problems. Deep learning algorithms are efficient, high performing, and an effective standard for solving these problems. In addition, with IoT, deep learning is in many emerging and developing domains of computer technology. Deep learning algorithms have brought a revolution in computer vision applications by introducing an efficient solution to several image processing-related problems that have long remained unresolved or moderately solved. Various significant IoT technologies in various industries, such as education, health, transportation, and security, combine IoT with deep learning for complex problem solving and the supported interaction between human beings and their surroundings. Examining the Impact of Deep Learning and IoT on Multi-Industry Applications provides insights on how deep learning, together with IoT, impacts various sectors such as healthcare, agriculture, cyber security, and social media analysis applications. The chapters present solutions to various real-world problems using these methods from various researchers’ points of view. While highlighting topics such as medical diagnosis, power consumption, livestock management, security, and social media analysis, this book is ideal for IT specialists, technologists, security analysts, medical practitioners, imaging specialists, diagnosticians, academicians, researchers, industrial experts, scientists, and undergraduate and postgraduate students who are working in the field of computer engineering, electronics, and electrical engineering.
Author: Saeid Sanei
Publisher: John Wiley & Sons
ISBN: 1118691237
Category : Science
Languages : en
Pages : 312
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Book Description
Electroencephalograms (EEGs) are becoming increasingly important measurements of brain activity and they have great potential for the diagnosis and treatment of mental and brain diseases and abnormalities. With appropriate interpretation methods they are emerging as a key methodology to satisfy the increasing global demand for more affordable and effective clinical and healthcare services. Developing and understanding advanced signal processing techniques for the analysis of EEG signals is crucial in the area of biomedical research. This book focuses on these techniques, providing expansive coverage of algorithms and tools from the field of digital signal processing. It discusses their applications to medical data, using graphs and topographic images to show simulation results that assess the efficacy of the methods. Additionally, expect to find: explanations of the significance of EEG signal analysis and processing (with examples) and a useful theoretical and mathematical background for the analysis and processing of EEG signals; an exploration of normal and abnormal EEGs, neurological symptoms and diagnostic information, and representations of the EEGs; reviews of theoretical approaches in EEG modelling, such as restoration, enhancement, segmentation, and the removal of different internal and external artefacts from the EEG and ERP (event-related potential) signals; coverage of major abnormalities such as seizure, and mental illnesses such as dementia, schizophrenia, and Alzheimer’s disease, together with their mathematical interpretations from the EEG and ERP signals and sleep phenomenon; descriptions of nonlinear and adaptive digital signal processing techniques for abnormality detection, source localization and brain-computer interfacing using multi-channel EEG data with emphasis on non-invasive techniques, together with future topics for research in the area of EEG signal processing. The information within EEG Signal Processing has the potential to enhance the clinically-related information within EEG signals, thereby aiding physicians and ultimately providing more cost effective, efficient diagnostic tools. It will be beneficial to psychiatrists, neurophysiologists, engineers, and students or researchers in neurosciences. Undergraduate and postgraduate biomedical engineering students and postgraduate epileptology students will also find it a helpful reference.
Author: Marek Kubicki
Publisher: Springer Nature
ISBN: 3030352064
Category : Medical
Languages : en
Pages : 432
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Book Description
This comprehensive book explains the importance of imaging techniques in exploring and understanding the role of brain abnormalities in schizophrenia. The findings obtained using individual imaging modalities and their biological interpretation are reviewed in detail, and updates are provided on methodology, testable hypotheses, limitations, and new directions for research. The coverage also includes important recent applications of neuroimaging to schizophrenia, for example in relation to non-pharmacological interventions, brain development, genetics, and prediction of treatment response and outcome. Written by world renowned experts in the field, the book will be invaluable to all who wish to learn about the newest and most important developments in neuroimaging research in schizophrenia, how these developments relate to the last 30 years of research, and how they can be leveraged to bring us closer to a cure for this devastating disorder. Neuroimaging in Schizophrenia will assist clinicians in navigating what is an extremely complex field and will be a source of insight and stimulation for researchers.
Author: David D. Luxton
Publisher: Academic Press
ISBN: 0128007923
Category : Psychology
Languages : en
Pages : 309
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Book Description
Artificial Intelligence in Behavioral and Mental Health Care summarizes recent advances in artificial intelligence as it applies to mental health clinical practice. Each chapter provides a technical description of the advance, review of application in clinical practice, and empirical data on clinical efficacy. In addition, each chapter includes a discussion of practical issues in clinical settings, ethical considerations, and limitations of use. The book encompasses AI based advances in decision-making, in assessment and treatment, in providing education to clients, robot assisted task completion, and the use of AI for research and data gathering. This book will be of use to mental health practitioners interested in learning about, or incorporating AI advances into their practice and for researchers interested in a comprehensive review of these advances in one source. - Summarizes AI advances for use in mental health practice - Includes advances in AI based decision-making and consultation - Describes AI applications for assessment and treatment - Details AI advances in robots for clinical settings - Provides empirical data on clinical efficacy - Explores practical issues of use in clinical settings
Author: Martha E. Shenton
Publisher: Cambridge University Press
ISBN: 1139493698
Category : Medical
Languages : en
Pages : 591
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Book Description
An informative and comprehensive review from the leading researchers in the field, this book provides a complete one-stop guide to neuroimaging techniques and their application to a wide range of neuropsychiatric disorders. For each disorder or group of disorders, separate chapters review the most up-to-date findings from structural imaging, functional imaging and/or molecular imaging. Each section ends with an overview from a internationally-renowned luminary in the field, addressing the question of 'What do we know and where are we going?' Richly illustrated throughout, each chapter includes a 'summary box', providing readers with explicit take-home messages. This is an essential resource for clinicians, researchers and trainees who want to learn how neuroimaging tools lead to new discoveries about brain and behaviour associations in neuropsychiatric disorders.
