Deep Learning for Neurological Disorders in Children PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Deep Learning for Neurological Disorders in Children PDF full book. Access full book title Deep Learning for Neurological Disorders in Children by Saman Sargolzaei. Download full books in PDF and EPUB format.
Author: Saman Sargolzaei
Publisher: Frontiers Media SA
ISBN: 2832508480
Category : Science
Languages : en
Pages : 134
Get Book Here
Book Description
Author: Saman Sargolzaei
Publisher: Frontiers Media SA
ISBN: 2832508480
Category : Science
Languages : en
Pages : 134
Get Book Here
Book Description
Author: Paul, Sudip
Publisher: IGI Global
ISBN: 1522585680
Category : Medical
Languages : en
Pages : 392
Get Book Here
Book Description
While doctors and physicians are more than capable of detecting diseases of the brain, the most agile human mind cannot compete with the processing power of modern technology. Utilizing algorithmic systems in healthcare in this way may provide a way to treat neurological diseases before they happen. Early Detection of Neurological Disorders Using Machine Learning Systems provides innovative insights into implementing smart systems to detect neurological diseases at a faster rate than by normal means. The topics included in this book are artificial intelligence, data analysis, and biomedical informatics. It is designed for clinicians, doctors, neurologists, physiotherapists, neurorehabilitation specialists, scholars, academics, and students interested in topics centered on biomedical engineering, bio-electronics, medical electronics, physiology, neurosciences, life sciences, and physics.
Author: D. Jude Hemanth
Publisher: Academic Press
ISBN: 0128222727
Category : Science
Languages : en
Pages : 322
Get Book Here
Book Description
Handbook of Decision Support Systems for Neurological Disorders provides readers with complete coverage of advanced computer-aided diagnosis systems for neurological disorders. While computer-aided decision support systems for different medical imaging modalities are available, this is the first book to solely concentrate on decision support systems for neurological disorders. Due to the increase in the prevalence of diseases such as Alzheimer, Parkinson's and Dementia, this book will have significant importance in the medical field. Topics discussed include recent computational approaches, different types of neurological disorders, deep convolution neural networks, generative adversarial networks, auto encoders, recurrent neural networks, and modified/hybrid artificial neural networks. - Includes applications of computer intelligence and decision support systems for the diagnosis and analysis of a variety of neurological disorders - Presents in-depth, technical coverage of computer-aided systems for tumor image classification, Alzheimer's disease detection, dementia detection using deep belief neural networks, and morphological approaches for stroke detection - Covers disease diagnosis for cerebral palsy using auto-encoder approaches, contrast enhancement for performance enhanced diagnosis systems, autism detection using fuzzy logic systems, and autism detection using generative adversarial networks - Written by engineers to help engineers, computer scientists, researchers and clinicians understand the technology and applications of decision support systems for neurological disorders
Author: Jyotismita Chaki
Publisher: CRC Press
ISBN: 1000872173
Category : Computers
Languages : en
Pages : 237
Get Book Here
Book Description
This book is based on deep learning approaches used for the diagnosis of neurological disorders, including basics of deep learning algorithms using diagrams, data tables, and practical examples, for diagnosis of neurodegenerative and neurodevelopmental disorders. It includes application of feed-forward neural networks, deep generative models, convolutional neural networks, graph convolutional networks, and recurrent neural networks in the field of diagnosis of neurological disorders. Along with this, data preprocessing including scaling, correction, trimming, and normalization is also included. Offers a detailed description of the deep learning approaches used for the diagnosis of neurological disorders. Demonstrates concepts of deep learning algorithms using diagrams, data tables, and examples for the diagnosis of neurodegenerative, neurodevelopmental, and psychiatric disorders. Helps build, train, and deploy different types of deep architectures for diagnosis. Explores data preprocessing techniques involved in diagnosis. Includes real-time case studies and examples. This book is aimed at graduate students and researchers in biomedical imaging and machine learning.
Author: Robert Melillo
Publisher: Penguin
ISBN: 9780399534751
Category : Family & Relationships
Languages : en
Pages : 292
Get Book Here
Book Description
Offering a bold new understanding of the causes of such disorders as autism, ADHD, Asperger's, dyslexia, and OCD, an effective drug-free program addresses both the symptoms and causes of conditions involving a disconnection between the left and right sides of the developing brain, with customizable exercises, behavior modification advice, nutritional guidelines, and more.
Author: Juerg Hodler
Publisher: Springer Nature
ISBN: 303038490X
Category : Medical
Languages : en
Pages : 252
Get Book Here
Book Description
This open access book offers an essential overview of brain, head and neck, and spine imaging. Over the last few years, there have been considerable advances in this area, driven by both clinical and technological developments. Written by leading international experts and teachers, the chapters are disease-oriented and cover all relevant imaging modalities, with a focus on magnetic resonance imaging and computed tomography. The book also includes a synopsis of pediatric imaging. IDKD books are rewritten (not merely updated) every four years, which means they offer a comprehensive review of the state-of-the-art in imaging. The book is clearly structured and features learning objectives, abstracts, subheadings, tables and take-home points, supported by design elements to help readers navigate the text. It will particularly appeal to general radiologists, radiology residents, and interventional radiologists who want to update their diagnostic expertise, as well as clinicians from other specialties who are interested in imaging for their patient care.
Author: Adam Kirton
Publisher: Academic Press
ISBN: 0128020385
Category : Medical
Languages : en
Pages : 504
Get Book Here
Book Description
Pediatric Brain Stimulation: Mapping and Modulating the Developing Brain presents the latest on this rapidly expanding field that has seen an exponential growth in publications over the past 10 years. Non-invasive modalities like TMS can painlessly map and measure complex neurophysiology in real patients. Neuromodulatory applications like rTMS and tDCS carry increasingly proven therapeutic applications. Rapidly advancing technological methodologies are increasing opportunities and indications. Despite all these benefits, applications in the more plastic developing brains of children are only just emerging. This book provides a comprehensive overview of brain stimulation in children. Chapters include Transcranial Magnetic Stimulation (TMS) fundamentals, brain stimulation in pediatric neurological conditions, and invasive brain stimulation. The main audience for this research will be those interested in applying brain stimulation technologies to advance clinical research and patient care, although a wide variety of clinicians and scientist will find this to be a valuable reference on brain stimulation with specific chapters on a variety of conditions. - Provides an overview of recent findings and knowledge of pediatric brain stimulation and the developing brain - Edited by renowned leaders in the field of pediatric brain stimulation - Presents a great resource for basic and clinical scientists and practitioners in neuroscience, neurology, neurosurgery, and psychiatry
Author: Virginia Ng
Publisher: IOS Press
ISBN: 9781586033446
Category :
Languages : en
Pages : 268
Get Book Here
Book Description
Author: Erik R. Ranschaert
Publisher: Springer
ISBN: 3319948784
Category : Medical
Languages : en
Pages : 369
Get Book Here
Book Description
This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.
Author: Le Lu
Publisher: Springer Nature
ISBN: 3030139697
Category : Computers
Languages : en
Pages : 452
Get Book Here
Book Description
This book reviews the state of the art in deep learning approaches to high-performance robust disease detection, robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities), and the construction and mining of large-scale radiology databases. It particularly focuses on the application of convolutional neural networks, and on recurrent neural networks like LSTM, using numerous practical examples to complement the theory. The book’s chief features are as follows: It highlights how deep neural networks can be used to address new questions and protocols, and to tackle current challenges in medical image computing; presents a comprehensive review of the latest research and literature; and describes a range of different methods that employ deep learning for object or landmark detection tasks in 2D and 3D medical imaging. In addition, the book examines a broad selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to text and image deep embedding for a large-scale chest x-ray image database; and discusses how deep learning relational graphs can be used to organize a sizable collection of radiology findings from real clinical practice, allowing semantic similarity-based retrieval. The intended reader of this edited book is a professional engineer, scientist or a graduate student who is able to comprehend general concepts of image processing, computer vision and medical image analysis. They can apply computer science and mathematical principles into problem solving practices. It may be necessary to have a certain level of familiarity with a number of more advanced subjects: image formation and enhancement, image understanding, visual recognition in medical applications, statistical learning, deep neural networks, structured prediction and image segmentation.
