Download or read book Machine Learning Based Autism Detection Using Brain Imaging written by Gajendra Jung Katuwal and published by . This book was released on 2017 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Autism Spectrum Disorder (ASD) is a group of heterogeneous developmental disabilities that manifest in early childhood. Currently, ASD is primarily diagnosed by assessing the behavioral and intellectual abilities of a child. This behavioral diagnosis can be subjective, time consuming, inconclusive, does not provide insight on the underlying etiology, and is not suitable for early detection. Diagnosis based on brain magnetic resonance imaging (MRI)—a widely used non- invasive tool—can be objective, can help understand the brain alterations in ASD, and can be suitable for early diagnosis. However, the brain morphological findings in ASD from MRI studies have been inconsistent. Moreover, there has been limited success in machine learning based ASD detection using MRI derived brain features. In this thesis, we begin by demonstrating that the low success in ASD detection and the inconsistent findings are likely attributable to the heterogeneity of brain alterations in ASD. We then show that ASD detection can be significantly improved by mitigating the heterogeneity with the help of behavioral and demographics information. Here we demonstrate that finding brain markers in well-defined sub-groups of ASD is easier and more insightful than identifying markers across the whole spectrum. Finally, our study focused on brain MRI of a pediatric cohort (3 to 4 years) and achieved a high classification success (AUC of 95%). Results of this study indicate three main alterations in early ASD brains: 1) abnormally large ventricles, 2) highly folded cortices, and 3) low image intensity in white matter regions suggesting myelination deficits indicative of decreased structural connectivity. Results of this thesis demonstrate that the meaningful brain markers of ASD can be extracted by applying machine learning techniques on brain MRI data. This data-driven technique can be a powerful tool for early detection and understanding brain anatomical underpinnings of ASD."--Abstract.

Download or read book Brain Connectivity in Autism written by Rajesh K. Kana and published by Frontiers E-books. This book was released on 2014-09-23 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Neural Engineering Techniques for Autism Spectrum Disorder written by Ayman S. El-Baz and published by Academic Press. This book was released on 2021-07-16 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural Engineering for Autism Spectrum Disorder, Volume One: Imaging and Signal Analysis Techniques presents the latest advances in neural engineering and biomedical engineering as applied to the clinical diagnosis and treatment of Autism Spectrum Disorder (ASD). Advances in the role of neuroimaging, infrared spectroscopy, sMRI, fMRI, DTI, social behaviors and suitable data analytics useful for clinical diagnosis and research applications for Autism Spectrum Disorder are covered, including relevant case studies. The application of brain signal evaluation, EEG analytics, feature selection, and analysis of blood oxygen level-dependent (BOLD) signals are presented for detection and estimation of the degree of ASD. Presents applications of Neural Engineering and other Machine Learning techniques for the diagnosis of Autism Spectrum Disorder (ASD) Includes in-depth technical coverage of imaging and signal analysis techniques, including coverage of functional MRI, neuroimaging, infrared spectroscopy, sMRI, fMRI, DTI, and neuroanatomy of autism Covers Signal Analysis for the detection and estimation of Autism Spectrum Disorder (ASD), including brain signal analysis, EEG analytics, feature selection, and analysis of blood oxygen level-dependent (BOLD) signals for ASD Written to help engineers, computer scientists, researchers and clinicians understand the technology and applications of Neural Engineering for the detection and diagnosis of Autism Spectrum Disorder (ASD)

Download or read book Artificial Intelligence for Accurate Analysis and Detection of Autism Spectrum Disorder written by Kautish, Sandeep and published by IGI Global. This book was released on 2021-06-25 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Autism spectrum disorder (ASD) is known as a neuro-disorder in which a person may face problems in interaction and communication with people, amongst other challenges. As per medical experts, ASD can be diagnosed at any stage or age but is often noticeable within the first two years of life. If caught early enough, therapies and services can be provided at this early stage instead of waiting until it is too late. ASD occurrences appear to have increased over the last couple of years leading to the need for more research in the field. It is crucial to provide researchers and clinicians with the most up-to-date information on the clinical features, etiopathogenesis, and therapeutic strategies for patients as well as to shed light on the other psychiatric conditions often associated with ASD. In addition, it is equally important to understand how to detect ASD in individuals for accurate diagnosing and early detection. Artificial Intelligence for Accurate Analysis and Detection of Autism Spectrum Disorder discusses the early detection and diagnosis of autism spectrum disorder enabled by artificial intelligence technologies, applications, and therapies. This book will focus on the early diagnosis of ASD through artificial intelligence, such as deep learning and machine learning algorithms, for confirming diagnosis or suggesting the need for further evaluation of individuals. The chapters will also discuss the use of artificial intelligence technologies, such as medical robots, for enhancing the communication skills and the social and emotional skills of children who have been diagnosed with ASD. This book is ideally intended for IT specialists, data scientists, academicians, scholars, researchers, policymakers, medical practitioners, and students interested in how artificial intelligence is impacting the diagnosis and treatment of autism spectrum disorder.

Download or read book Intelligent Diagnosis with Adversarial Machine Learning in Multimodal Biomedical Brain Images written by Yuhui Zheng and published by Frontiers Media SA. This book was released on 2021-09-23 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Enabling Technology for Neurodevelopmental Disorders written by Tanu Wadhera and published by Taylor & Francis. This book was released on 2022-04-20 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: This cutting-edge volume explores how technological tools can be designed, engineered and implemented to assess and support individuals with neurodevelopmental disorders from diagnosis through to rehabilitation. Tanu Wadhera and Deepti Kakkar and their expert contributors focus on technological tools as equalizers in Neurodevelopmental disorders (NDDs) at every stage, the importance of demand-specific design, and how we can best engineer and deploy both invasive and non-invasive individual-centered approaches that support and connect individuals. Considering the perspectives of patients, clinicians and technologists, it explores key topics including design and evaluation of platforms for tech-tools, automated diagnosis, brain imaging techniques, tech-diagnostic frameworks with AI and machine learning, sensing technology, smart brain prosthetics, gamification, alternative communication devices, and education tools and interactive toys. Outlining future challenges for research, Enabling Technology for Neurodevelopmental Disorders is useful for scholars and professionals in psychology, technology, engineering and medicine concerned with design, development and evaluation of a range of assistive technological tools.

Download or read book A Machine Learning Study of Intrinsic Functional Connectivity in Autism Spectrum Disorders written by and published by . This book was released on 2014 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite consensus on the neurological nature of autism spectrum disorders (ASD), brain biomarkers remain unknown and diagnosis continues to be based on behavioral criteria. Growing evidence suggests that brain abnormalities in ASD occur at the level of interconnected networks; however, previous attempts using functional connectivity data for diagnostic classification have reached only moderate accuracy. We selected 252 low-motion resting-state functional MRI (rs-fMRI) scans from the Autism Brain Imaging Data Exchange (ABIDE) including typically developing (TD) and ASD participants (n=126 each), matched for age, non-verbal IQ, and head motion. A matrix of functional connectivities between 220 functionally defined regions of interest was used for diagnostic classification, implementing several machine learning tools. While support vector machines in combination with particle swarm optimization and recursive feature elimination performed modestly (with accuracies for validation data sets

Download or read book 2021 6th International Conference for Convergence in Technology I2CT written by IEEE Staff and published by . This book was released on 2021-04-02 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Microwave Wireless Networking Computational Intelligence Advanced Computing Electronics and Interdisciplinary Data Communication and Networking Renewable and Sustainable Energy Power Engineering and Control System Signal and Image Processing Communication System Biomedical Engineering Design, Materials and Manufacturing Fleet Technologies

Download or read book Machine Learning in Radiation Oncology written by Issam El Naqa and published by Springer. This book was released on 2015-06-19 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: ​This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.

Download or read book Emerging Technologies for Healthcare written by Monika Mangla and published by John Wiley & Sons. This book was released on 2021-08-17 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Emerging Technologies for Healthcare” begins with an IoT-based solution for the automated healthcare sector which is enhanced to provide solutions with advanced deep learning techniques. The book provides feasible solutions through various machine learning approaches and applies them to disease analysis and prediction. An example of this is employing a three-dimensional matrix approach for treating chronic kidney disease, the diagnosis and prognostication of acquired demyelinating syndrome (ADS) and autism spectrum disorder, and the detection of pneumonia. In addition, it provides healthcare solutions for post COVID-19 outbreaks through various suitable approaches, Moreover, a detailed detection mechanism is discussed which is used to devise solutions for predicting personality through handwriting recognition; and novel approaches for sentiment analysis are also discussed with sufficient data and its dimensions. This book not only covers theoretical approaches and algorithms, but also contains the sequence of steps used to analyze problems with data, processes, reports, and optimization techniques. It will serve as a single source for solving various problems via machine learning algorithms.

Download or read book Magnetic Resonance Brain Imaging written by Jörg Polzehl and published by Springer Nature. This book was released on 2019-09-25 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the modeling and analysis of magnetic resonance imaging (MRI) data acquired from the human brain. The data processing pipelines described rely on R. The book is intended for readers from two communities: Statisticians who are interested in neuroimaging and looking for an introduction to the acquired data and typical scientific problems in the field; and neuroimaging students wanting to learn about the statistical modeling and analysis of MRI data. Offering a practical introduction to the field, the book focuses on those problems in data analysis for which implementations within R are available. It also includes fully worked examples and as such serves as a tutorial on MRI analysis with R, from which the readers can derive their own data processing scripts. The book starts with a short introduction to MRI and then examines the process of reading and writing common neuroimaging data formats to and from the R session. The main chapters cover three common MR imaging modalities and their data modeling and analysis problems: functional MRI, diffusion MRI, and Multi-Parameter Mapping. The book concludes with extended appendices providing details of the non-parametric statistics used and the resources for R and MRI data.The book also addresses the issues of reproducibility and topics like data organization and description, as well as open data and open science. It relies solely on a dynamic report generation with knitr and uses neuroimaging data publicly available in data repositories. The PDF was created executing the R code in the chunks and then running LaTeX, which means that almost all figures, numbers, and results were generated while producing the PDF from the sources.

Download or read book Autism Imaging and Devices written by Manuel F. Casanova and published by CRC Press. This book was released on 2017-01-06 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers state-of-the-art medical image analysis approaches currently pursued in autism research. Chapters cover recent advances in diagnosis using structural neuroimaging. All aspects of imaging are included, such as electrophysiology (EEG, ERP, QEEG, and MEG), postmortem techniques, and advantages and difficulties of depositing/acquiring images in larger databases. The book incorporates 2D, 3D, and 4D imaging and advances scientific research within the broad field of autism imaging.

Download or read book Deep Learning in Medical Image Analysis written by Gobert Lee and published by Springer Nature. This book was released on 2020-02-06 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents cutting-edge research and applications of deep learning in a broad range of medical imaging scenarios, such as computer-aided diagnosis, image segmentation, tissue recognition and classification, and other areas of medical and healthcare problems. Each of its chapters covers a topic in depth, ranging from medical image synthesis and techniques for muskuloskeletal analysis to diagnostic tools for breast lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical image analysis and highlights issues and challenges encountered by researchers and clinicians, surveying and discussing practical approaches in general and in the context of specific problems. Academics, clinical and industry researchers, as well as young researchers and graduate students in medical imaging, computer-aided-diagnosis, biomedical engineering and computer vision will find this book a great reference and very useful learning resource.

Download or read book Proceedings of the 2nd International Conference on Computational and Bio Engineering written by S. Jyothi and published by Springer Nature. This book was released on 2021-09-27 with total page 774 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the peer-reviewed proceedings of the 2nd International Conference on Computational and Bioengineering (CBE 2020) jointly organized in virtual mode by the Department of Computer Science and the Department of BioScience & Sericulture, Sri Padmavati Mahila Visvavidyalayam (Women's University), Tirupati, Andhra Pradesh, India, during 4–5 December 2020. The book includes the latest research on advanced computational methodologies such as artificial intelligence, data mining and data warehousing, cloud computing, computational intelligence, soft computing, image processing, Internet of things, cognitive computing, wireless networks, social networks, big data analytics, machine learning, network security, computer networks and communications, bioinformatics, biocomputing/biometrics, computational biology, biomaterials, bioengineering, and medical and biomedical informatics.

Download or read book Development and Brain Systems in Autism written by Marcel Adam Just and published by Psychology Press. This book was released on 2013 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volume covers several perspectives on autism which bring together the most recent scientific views of the nature of this disorder. A number of themes organize major developments and emerging areas in autism. The book is essential for reseachers and practitioners who require a state-of-the-art resource on autism.

Download or read book Computational Vision and Bio Inspired Computing written by S. Smys and published by Springer Nature. This book was released on 2021-06-14 with total page 871 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes selected papers from the 4th International Conference on Computational Vision and Bio Inspired Computing (ICCVBIC 2020), held in Coimbatore, India, from November 19 to 20, 2020. This proceedings book presents state-of-the-art research innovations in computational vision and bio-inspired techniques. The book reveals the theoretical and practical aspects of bio-inspired computing techniques, like machine learning, sensor-based models, evolutionary optimization and big data modeling and management that make use of effectual computing processes in the bio-inspired systems. As such it contributes to the novel research that focuses on developing bio-inspired computing solutions for various domains, such as human–computer interaction, image processing, sensor-based single processing, recommender systems and facial recognition, which play an indispensable part in smart agriculture, smart city, biomedical and business intelligence applications.

Download or read book 2021 8th International Conference on Smart Computing and Communications ICSCC written by IEEE Staff and published by . This book was released on 2021-07 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The conference will bring together experts from the Smart computing and Communication systems community to discuss the timely issue of smart computing and low energy system design This will provide a forum for sharing insights, experiences and interaction on various aspects of evolving technologies and patterns related to Computer Science, Information Technology, Electronics, and associated Energy Systems The conference provides a platform for not only to the researchers from Asia but also from other continents across the globe, making this conference more international and attractive for participants