Data Analysis For Neurodegenerative Disorders
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Data Analysis For Neurodegenerative Disorders
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Author : Deepika Koundal
language : en
Publisher: Springer Nature
Release Date : 2023-05-31
Data Analysis For Neurodegenerative Disorders written by Deepika Koundal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-31 with Medical categories.
This book explores the challenges involved in handling medical big data in the diagnosis of neurological disorders. It discusses how to optimally reduce the number of neuropsychological tests during the classification of these disorders by using feature selection methods based on the diagnostic information of enrolled subjects. The book includes key definitions/models and covers their applications in different types of signal/image processing for neurological disorder data. An extensive discussion on the possibility of enhancing the abilities of AI systems using the different data analysis is included. The book recollects several applicable basic preliminaries of the different AI networks and models, while also highlighting basic processes in image processing for various neurological disorders. It also reports on several applications to image processing and explores numerous topics concerning the role of big data analysis in addressing signal and image processing in various real-world scenarios involving neurological disorders. This cutting-edge book highlights the analysis of medical data, together with novel procedures and challenges for handling neurological signals and images. It will help engineers, researchers and software developers to understand the concepts and different models of AI and data analysis. To help readers gain a comprehensive grasp of the subject, it focuses on three key features: ● Presents outstanding concepts and models for using AI in clinical applications involving neurological disorders, with clear descriptions of image representation, feature extraction and selection. ● Highlights a range of techniques for evaluating the performance of proposed CAD systems for the diagnosis of neurological disorders. ● Examines various signal and image processing methods for efficient decision support systems. Soft computing, machine learning and optimization algorithms are also included to improve the CAD systems used.
Fundamental Statistical Methods For Analysis Of Alzheimer S And Other Neurodegenerative Diseases
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Author : Katherine E. Irimata
language : en
Publisher: JHU Press
Release Date : 2020-05-05
Fundamental Statistical Methods For Analysis Of Alzheimer S And Other Neurodegenerative Diseases written by Katherine E. Irimata and has been published by JHU Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-05 with Medical categories.
A statistics textbook that delivers essential data analysis techniques for Alzheimer's and other neurodegenerative diseases. Alzheimer's disease is a devastating condition that presents overwhelming challenges to patients and caregivers. In the face of this relentless and as-yet incurable disease, mastery of statistical analysis is paramount for anyone who must assess complex data that could improve treatment options. This unique book presents up-to-date statistical techniques commonly used in the analysis of data on Alzheimer's and other neurodegenerative diseases. With examples drawn from the real world that will make it accessible to disease researchers, practitioners, academics, and students alike, this volume • presents code for analyzing dementia data in statistical programs, including SAS, R, SPSS, and Stata • introduces statistical models for a range of data types, including continuous, categorical, and binary responses, as well as correlated data • draws on datasets from the National Alzheimer's Coordinating Center, a large relational database of standardized clinical and neuropathological research data • discusses advanced statistical methods, including hierarchical models, survival analysis, and multiple-membership • examines big data analytics and machine learning methods Easy to understand but sophisticated in its approach, Fundamental Statistical Methods for Analysis of Alzheimer's and Other Neurodegenerative Diseases will be a cornerstone for anyone looking for simplicity in understanding basic and advanced statistical data analysis topics. Allowing more people to aid in analyzing data—while promoting constructive dialogues with statisticians—this book will hopefully play an important part in unlocking the secrets of these confounding diseases.
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
Ai And Neuro Degenerative Diseases
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Author : Loveleen Gaur
language : en
Publisher: Springer Nature
Release Date :
Ai And Neuro Degenerative Diseases written by Loveleen Gaur and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Deep Learning Approaches For Early Diagnosis Of Neurodegenerative Diseases
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Author : Rodriguez, Raul Villamarin
language : en
Publisher: IGI Global
Release Date : 2024-02-14
Deep Learning Approaches For Early Diagnosis Of Neurodegenerative Diseases written by Rodriguez, Raul Villamarin and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-14 with Medical categories.
Within the context of global health challenges posed by intractable neurodegenerative diseases like Alzheimer's and Parkinson's, the significance of early diagnosis is critical for effective intervention, and scientists continue to discover new methods of detection. However, actual diagnosis goes beyond detection to include a significant analysis of combined data for many cases, which presents a challenge of several complicated calculations. Deep Learning Approaches for Early Diagnosis of Neurodegenerative Diseases stands as a groundbreaking work at the intersection of artificial intelligence and neuroscience. The book orchestrates a symphony of cutting-edge techniques and progressions in early detection by assembling eminent experts from the domains of deep learning and neurology. Through a harmonious blend of research areas and pragmatic applications, this monumental work charts the transformative course to revolutionize the landscape of early diagnosis and management of neurodegenerative disorders. Within the pages, readers will embark through the intricate landscape of neurodegenerative diseases, the fundamental underpinnings of deep learning, the nuances of neuroimaging data acquisition and preprocessing, the alchemy of feature extraction and representation learning, and the symphony of deep learning models tailored for neurodegenerative disease diagnosis. The book also delves into integrating multimodal data to augment diagnosis, the imperative of rigorously evaluating and validating deep learning models, and the ethical considerations and challenges entwined with deep learning for neurodegenerative diseases.
Neurodegenerative Diseases
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Author : Daniela Galimberti
language : en
Publisher: Springer
Release Date : 2018-03-15
Neurodegenerative Diseases written by Daniela Galimberti and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-15 with Medical categories.
This book gives an overview of the current knowledge on the most common neurodegenerative diseases, including Alzheimer’s disease, frontotemporal lobar degeneration, Lewy body dementia,Parkinson’s disease, amyotrophic lateral sclerosis, and additional less common neurodegenerative diseases. Both clinical and basic aspects of each disease are treated, including novel diagnostic criteria, old and new treatments, basic discoveries (genetics, epigenetics and molecular biology), and translation of basic research into biomarkers for early diagnosis, particularly to identify peripheral biomarkers. In addition, emerging data indicate that neurodegeneration seems to also be present in classically non-degenerative disorders. Therefore, a chapter about overlapping mechanisms between dementias and psychiatric disorders is included, as well as a description of the role of neurodegeneration in multiple sclerosis. Neurodegenerative Diseases is aimed at clinicians, particularly those working in academic hospitals. This multidisciplinary book will also be of interest to basic researchers in medical fields.
Multimodal Neuroimaging Computing For The Characterization Of Neurodegenerative Disorders
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Author : Sidong Liu
language : en
Publisher: Springer
Release Date : 2017-01-11
Multimodal Neuroimaging Computing For The Characterization Of Neurodegenerative Disorders written by Sidong Liu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-11 with Computers categories.
This thesis covers various facets of brain image computing methods and illustrates the scientific understanding of neurodegenerative disorders based on four general aspects of multimodal neuroimaging computing: neuroimaging data pre-processing, brain feature modeling, pathological pattern analysis, and translational model development. It demonstrates how multimodal neuroimaging computing techniques can be integrated and applied to neurodegenerative disease research and management, highlighting relevant examples and case studies. Readers will also discover a number of interesting extension topics in longitudinal neuroimaging studies, subject-centered analysis, and the brain connectome. As such, the book will benefit all health informatics postgraduates, neuroscience researchers, neurology and psychiatry practitioners, and policymakers who are interested in medical image computing and computer-assisted interventions. “br>
Handbook Of Research On Disease Prediction Through Data Analytics And Machine Learning
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Author : Rani, Geeta
language : en
Publisher: IGI Global
Release Date : 2020-10-16
Handbook Of Research On Disease Prediction Through Data Analytics And Machine Learning written by Rani, Geeta and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-16 with Medical categories.
By applying data analytics techniques and machine learning algorithms to predict disease, medical practitioners can more accurately diagnose and treat patients. However, researchers face problems in identifying suitable algorithms for pre-processing, transformations, and the integration of clinical data in a single module, as well as seeking different ways to build and evaluate models. The Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning is a pivotal reference source that explores the application of algorithms to making disease predictions through the identification of symptoms and information retrieval from images such as MRIs, ECGs, EEGs, etc. Highlighting a wide range of topics including clinical decision support systems, biomedical image analysis, and prediction models, this book is ideally designed for clinicians, physicians, programmers, computer engineers, IT specialists, data analysts, hospital administrators, researchers, academicians, and graduate and post-graduate students.
Imaging In Neurodegenerative Disorders
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Author : Luca Saba
language : en
Publisher: Oxford University Press, USA
Release Date : 2015
Imaging In Neurodegenerative Disorders written by Luca Saba and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Medical categories.
This text summarizes the latest developments in imaging techniques and other new diagnostic methods as applied to the neurodegenerative disorders.
Artificial Intelligence For Neurological Disorders
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Author : Ajith Abraham
language : en
Publisher: Academic Press
Release Date : 2022-09-23
Artificial Intelligence For Neurological Disorders written by Ajith Abraham and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-23 with Medical categories.
Artificial Intelligence for Neurological Disorders provides a comprehensive resource of state-of-the-art approaches for AI, big data analytics and machine learning-based neurological research. The book discusses many machine learning techniques to detect neurological diseases at the cellular level, as well as other applications such as image segmentation, classification and image indexing, neural networks and image processing methods. Chapters include AI techniques for the early detection of neurological disease and deep learning applications using brain imaging methods like EEG, MEG, fMRI, fNIRS and PET for seizure prediction or neuromuscular rehabilitation. The goal of this book is to provide readers with broad coverage of these methods to encourage an even wider adoption of AI, Machine Learning and Big Data Analytics for problem-solving and stimulating neurological research and therapy advances. Discusses various AI and ML methods to apply for neurological research Explores Deep Learning techniques for brain MRI images Covers AI techniques for the early detection of neurological diseases and seizure prediction Examines cognitive therapies using AI and Deep Learning methods