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Machine Learning And Interpretation In Neuroimaging
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Book Synopsis Machine Learning and Interpretation in Neuroimaging by : Georg Langs
Download or read book Machine Learning and Interpretation in Neuroimaging written by Georg Langs and published by Springer. This book was released on 2012-11-11 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain imaging brings together the technology, methodology, research questions and approaches of a wide range of scientific fields including physics, statistics, computer science, neuroscience, biology, and engineering. Thus, methodological and technological advances that enable us to obtain measurements, examine relationships across observations, and link these data to neuroscientific hypotheses happen in a highly interdisciplinary environment. The dynamic field of machine learning with its modern approach to data mining provides many relevant approaches for neuroscience and enables the exploration of open questions. This state-of-the-art survey offers a collection of papers from the Workshop on Machine Learning and Interpretation in Neuroimaging, MLINI 2011, held at the 25th Annual Conference on Neural Information Processing, NIPS 2011, in the Sierra Nevada, Spain, in December 2011. Additionally, invited speakers agreed to contribute reviews on various aspects of the field, adding breadth and perspective to the volume. The 32 revised papers were carefully selected from 48 submissions. At the interface between machine learning and neuroimaging the papers aim at shedding some light on the state of the art in this interdisciplinary field. They are organized in topical sections on coding and decoding, neuroscience, dynamcis, connectivity, and probabilistic models and machine learning.
Book Synopsis Machine Learning and Interpretation in Neuroimaging by : Irina Rish
Download or read book Machine Learning and Interpretation in Neuroimaging written by Irina Rish and published by Springer. This book was released on 2016-09-12 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the revised selected papers from the 4th International Workshop on Machine Learning and Interpretation in Neuroimaging, MLINI 2014, held in Montreal, QC, Canada, in December 2014 as a satellite event of the 11th annual conference on Neural Information Processing Systems, NIPS 2014. The 10 MLINI 2014 papers presented in this volume were carefully reviewed and selected from 17 submissions. They were organized in topical sections named: networks and decoding; speech; clinics and cognition; and causality and time-series. In addition, the book contains the 3 best papers presented at MLINI 2013.
Book Synopsis Machine Learning and Other Artificial Intelligence Applications, An Issue of Neuroimaging Clinics of North America, E-Book by : Reza Forghani
Download or read book Machine Learning and Other Artificial Intelligence Applications, An Issue of Neuroimaging Clinics of North America, E-Book written by Reza Forghani and published by Elsevier Health Sciences. This book was released on 2020-10-23 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This issue of Neuroimaging Clinics of North America focuses on Artificial Intelligence and Machine Learning and is edited by Dr. Reza Forghani. Articles will include: A Brief History of Artificial Intelligence; Evolution of Approaches for Computerized Image Analysis; Overview of Machine Learning Part 1: Classic Approaches; Overview of Machine Learning Part 2: Artificial Neural Networks & Deep Learning; Overview of Natural Language Processing; Artificial Intelligence & Stroke Imaging: An East Coast Perspective; Artificial Intelligence & Stroke Imaging: A West Coast Perspective; Artificial Intelligence Applications for Brain Tumor Imaging; Diverse Applications of Artificial Intelligence in Neuroradiology; Artificial Intelligence Applications for Head and Neck Imaging; Artificial Intelligence Applications for Predictive Analytics and Workflow Optimization; Artificial Intelligence, Advanced Visualization, and 3D Printing; Ethical & Legal Considerations for Artificial Intelligence; Comprehensive (or 360) Artificial Intelligence: Beyond Image Interpretation Alone, and more!
Book Synopsis Understanding and Interpreting Machine Learning in Medical Image Computing Applications by : Danail Stoyanov
Download or read book Understanding and Interpreting Machine Learning in Medical Image Computing Applications written by Danail Stoyanov and published by Springer. This book was released on 2018-10-23 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed joint proceedings of the First International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2018, the First International Workshop on Deep Learning Fails, DLF 2018, and the First International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 4 full MLCN papers, the 6 full DLF papers, and the 6 full iMIMIC papers included in this volume were carefully reviewed and selected. The MLCN contributions develop state-of-the-art machine learning methods such as spatio-temporal Gaussian process analysis, stochastic variational inference, and deep learning for applications in Alzheimer's disease diagnosis and multi-site neuroimaging data analysis; the DLF papers evaluate the strengths and weaknesses of DL and identify the main challenges in the current state of the art and future directions; the iMIMIC papers cover a large range of topics in the field of interpretability of machine learning in the context of medical image analysis.
Book Synopsis Machine Learning and Deep Learning in Neuroimaging Data Analysis by : Anitha S. Pillai
Download or read book Machine Learning and Deep Learning in Neuroimaging Data Analysis written by Anitha S. Pillai and published by CRC Press. This book was released on 2024-02-15 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning (ML) and deep learning (DL) have become essential tools in healthcare. They are capable of processing enormous amounts of data to find patterns and are also adopted into methods that manage and make sense of healthcare data, either electronic healthcare records or medical imagery. This book explores how ML/DL can assist neurologists in identifying, classifying or predicting neurological problems that require neuroimaging. With the ability to model high-dimensional datasets, supervised learning algorithms can help in relating brain images to behavioral or clinical observations and unsupervised learning can uncover hidden structures/patterns in images. Bringing together artificial intelligence (AI) experts as well as medical practitioners, these chapters cover the majority of neuro problems that use neuroimaging for diagnosis, along with case studies and directions for future research.
Book Synopsis Artificial Intelligence for Medical Image Analysis of NeuroImaging Data by : Nianyin Zeng
Download or read book Artificial Intelligence for Medical Image Analysis of NeuroImaging Data written by Nianyin Zeng and published by Frontiers Media SA. This book was released on 2020-07-03 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Machine Learning in Clinical Neuroscience by : Victor E. Staartjes
Download or read book Machine Learning in Clinical Neuroscience written by Victor E. Staartjes and published by Springer Nature. This book was released on 2021-12-03 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book bridges the gap between data scientists and clinicians by introducing all relevant aspects of machine learning in an accessible way, and will certainly foster new and serendipitous applications of machine learning in the clinical neurosciences. Building from the ground up by communicating the foundational knowledge and intuitions first before progressing to more advanced and specific topics, the book is well-suited even for clinicians without prior machine learning experience. Authored by a wide array of experienced global machine learning groups, the book is aimed at clinicians who are interested in mastering the basics of machine learning and who wish to get started with their own machine learning research. The volume is structured in two major parts: The first uniquely introduces all major concepts in clinical machine learning from the ground up, and includes step-by-step instructions on how to correctly develop and validate clinical prediction models. It also includes methodological and conceptual foundations of other applications of machine learning in clinical neuroscience, such as applications of machine learning to neuroimaging, natural language processing, and time series analysis. The second part provides an overview of some state-of-the-art applications of these methodologies. The Machine Intelligence in Clinical Neuroscience (MICN) Laboratory at the Department of Neurosurgery of the University Hospital Zurich studies clinical applications of machine intelligence to improve patient care in clinical neuroscience. The group focuses on diagnostic, prognostic and predictive analytics that aid in decision-making by increasing objectivity and transparency to patients. Other major interests of our group members are in medical imaging, and intraoperative applications of machine vision.
Book Synopsis Machine Learning in Clinical Neuroimaging by : Ahmed Abdulkadir
Download or read book Machine Learning in Clinical Neuroimaging written by Ahmed Abdulkadir and published by Springer Nature. This book was released on 2021-09-22 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2021, held on September 27, 2021, in conjunction with MICCAI 2021. The workshop was held virtually due to the COVID-19 pandemic. The 17 papers presented in this book were carefully reviewed and selected from 27 submissions. They were organized in topical sections named: computational anatomy and brain networks and time series.
Book Synopsis Data Science for Neuroimaging by : Ariel Rokem
Download or read book Data Science for Neuroimaging written by Ariel Rokem and published by Princeton University Press. This book was released on 2023-11-07 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data science methods and tools—including programming, data management, visualization, and machine learning—and their application to neuroimaging research As neuroimaging turns toward data-intensive discovery, researchers in the field must learn to access, manage, and analyze datasets at unprecedented scales. Concerns about reproducibility and increased rigor in reporting of scientific results also demand higher standards of computational practice. This book offers neuroimaging researchers an introduction to data science, presenting methods, tools, and approaches that facilitate automated, reproducible, and scalable analysis and understanding of data. Through guided, hands-on explorations of openly available neuroimaging datasets, the book explains such elements of data science as programming, data management, visualization, and machine learning, and describes their application to neuroimaging. Readers will come away with broadly relevant data science skills that they can easily translate to their own questions. • Fills the need for an authoritative resource on data science for neuroimaging researchers • Strong emphasis on programming • Provides extensive code examples written in the Python programming language • Draws on openly available neuroimaging datasets for examples • Written entirely in the Jupyter notebook format, so the code examples can be executed, modified, and re-executed as part of the learning process
Book Synopsis OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging by : Luping Zhou
Download or read book OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging written by Luping Zhou and published by Springer Nature. This book was released on 2019-10-10 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Workshop on Context-Aware Surgical Theaters, OR 2.0 2019, and the Second International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. For OR 2.0 all 6 submissions were accepted for publication. They aim to highlight the potential use of machine vision and perception, robotics, surgical simulation and modeling, multi-modal data fusion and visualization, image analysis, advanced imaging, advanced display technologies, human-computer interfaces, sensors, wearable and implantable electronics and robots, visual attention models, cognitive models, decision support networks to enhance surgical procedural assistance, context-awareness and team communication in the operating theater, human-robot collaborative systems, and surgical training and assessment. MLCN 2019 accepted 6 papers out of 7 submissions for publication. They focus on addressing the problems of applying machine learning to large and multi-site clinical neuroimaging datasets. The workshop aimed to bring together experts in both machine learning and clinical neuroimaging to discuss and hopefully bridge the existing challenges of applied machine learning in clinical neuroscience.
Book Synopsis Explainable AI: Interpreting, Explaining and Visualizing Deep Learning by : Wojciech Samek
Download or read book Explainable AI: Interpreting, Explaining and Visualizing Deep Learning written by Wojciech Samek and published by Springer Nature. This book was released on 2019-09-10 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.
Book Synopsis Intelligent Diagnosis with Adversarial Machine Learning in Multimodal Biomedical Brain Images by : Yuhui Zheng
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:
Book Synopsis Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology by : Seyed Mostafa Kia
Download or read book Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology written by Seyed Mostafa Kia and published by Springer Nature. This book was released on 2020-12-30 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2020, and the Second International Workshop on Radiogenomics in Neuro-oncology, RNO-AI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020.* For MLCN 2020, 18 papers out of 28 submissions were accepted for publication. The accepted papers present novel contributions in both developing new machine learning methods and applications of existing methods to solve challenging problems in clinical neuroimaging. For RNO-AI 2020, all 8 submissions were accepted for publication. They focus on addressing the problems of applying machine learning to large and multi-site clinical neuroimaging datasets. The workshop aimed to bring together experts in both machine learning and clinical neuroimaging to discuss and hopefully bridge the existing challenges of applied machine learning in clinical neuroscience. *The workshops were held virtually due to the COVID-19 pandemic.
Book Synopsis Machine Learning in Clinical Neuroimaging by : Ahmed Abdulkadir
Download or read book Machine Learning in Clinical Neuroimaging written by Ahmed Abdulkadir and published by Springer Nature. This book was released on 2022-10-07 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2022, held in Conjunction with MICCAI 2022, Singapore in September 2022. The book includes 17 papers which were carefully reviewed and selected from 23 full-length submissions. The 5th international workshop on Machine Learning in Clinical Neuroimaging (MLCN2022) aims to bring together the top researchers in both machine learning and clinical neuroscience as well as tech-savvy clinicians to address two main challenges: 1) development of methodological approaches for analyzing complex and heterogeneous neuroimaging data (machine learning track); and 2) filling the translational gap in applying existing machine learning methods in clinical practices (clinical neuroimaging track). The papers are categorzied into topical sub-headings: Morphometry; Diagnostics, and Aging, and Neurodegeneration.
Book Synopsis Artificial Intelligence and Machine Learning, an Issue of Neuroimaging Clinics of North America, Volume 30-4 by : Reza Forghani
Download or read book Artificial Intelligence and Machine Learning, an Issue of Neuroimaging Clinics of North America, Volume 30-4 written by Reza Forghani and published by Elsevier. This book was released on 2020-11-30 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: This issue of Neuroimaging Clinics of North America focuses on Artificial Intelligence and Machine Learning and is edited by Dr. Reza Forghani. Articles will include: A Brief History of Artificial Intelligence; Evolution of Approaches for Computerized Image Analysis; Overview of Machine Learning Part 1: Classic Approaches; Overview of Machine Learning Part 2: Artificial Neural Networks & Deep Learning; Overview of Natural Language Processing; Artificial Intelligence & Stroke Imaging: An East Coast Perspective; Artificial Intelligence & Stroke Imaging: A West Coast Perspective; Artificial Intelligence Applications for Brain Tumor Imaging; Diverse Applications of Artificial Intelligence in Neuroradiology; Artificial Intelligence Applications for Head and Neck Imaging; Artificial Intelligence Applications for Predictive Analytics and Workflow Optimization; Artificial Intelligence, Advanced Visualization, and 3D Printing; Ethical & Legal Considerations for Artificial Intelligence; Comprehensive (or 360) Artificial Intelligence: Beyond Image Interpretation Alone, and more!
Book Synopsis Handbook of Neuroimaging Data Analysis by : Emery Peterson
Download or read book Handbook of Neuroimaging Data Analysis written by Emery Peterson and published by American Medical Publishers. This book was released on 2023-09-19 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neuroimaging is the use of quantitative methods to study the structure and function of the central nervous system. It is basically developed for scientifically studying the healthy human brain in a non-invasive manner. It is utilized for quantitative studies of psychiatric illness and brain diseases. It can be categorized into structural imaging and functional imaging. Structural imaging is used for quantifying the structure of the brain utilizing voxel based morphometry, whereas in functional imaging, brain function is studied by utilizing techniques such as MEG and PET. Techniques of functional brain imaging such as functional magnetic resonance imaging are commonly utilized techniques in neuroimaging. Medical imaging of the brain has various distinguishing features, which increases the difficulty in the assessment. Various artificial intelligence techniques like expert systems, machine learning, knowledge representation, robotics and perception, deep neural networks, reinforcement learning, and evolutionary computation can be used for better interpretation of the brain images. This book unravels the recent studies on neuroimaging data analysis. It is a resource guide for experts as well as students.
Book Synopsis Graph Learning for Brain Imaging by : Feng Liu
Download or read book Graph Learning for Brain Imaging written by Feng Liu and published by Frontiers Media SA. This book was released on 2022-09-30 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt:
