Machine Learning In Clinical Neuroscience
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Machine Learning In Clinical Neuroscience
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Author : Victor E. Staartjes
language : en
Publisher: Springer Nature
Release Date : 2021-12-03
Machine Learning In Clinical Neuroscience written by Victor E. Staartjes and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-03 with Medical categories.
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.
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
Machine Learning In Clinical Neuroimaging And Radiogenomics In Neuro Oncology
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Author : Seyed Mostafa Kia
language : en
Publisher: Springer Nature
Release Date : 2020-12-30
Machine Learning In Clinical Neuroimaging And Radiogenomics In Neuro Oncology written by Seyed Mostafa Kia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-30 with Computers categories.
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.
Machine Learning In Clinical Neuroimaging
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Author : Ahmed Abdulkadir
language : en
Publisher: Springer Nature
Release Date : 2021-09-22
Machine Learning In Clinical Neuroimaging written by Ahmed Abdulkadir and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-22 with Computers categories.
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.
Data Driven Computational Neuroscience
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Author : Concha Bielza
language : en
Publisher: Cambridge University Press
Release Date : 2020-11-26
Data Driven Computational Neuroscience written by Concha Bielza and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-26 with Computers categories.
Trains researchers and graduate students in state-of-the-art statistical and machine learning methods to build models with real-world data.
Understanding And Interpreting Machine Learning In Medical Image Computing Applications
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Author : Danail Stoyanov
language : en
Publisher: Springer
Release Date : 2018-10-23
Understanding And Interpreting Machine Learning In Medical Image Computing Applications written by Danail Stoyanov and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-23 with Computers categories.
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.
Computational Neurosurgery
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Author : Antonio Di Ieva
language : en
Publisher: Springer Nature
Release Date : 2024-11-10
Computational Neurosurgery written by Antonio Di Ieva and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-10 with Science categories.
This comprehensive and authoritative reference presents the state-of-the-art computational methods applied to the field of neurosurgery. The book brings together leading neuroscientists, neurosurgeons, mathematicians, computer scientists, engineers, ethicists and lawyers, to open the new frontier of computational neurosurgery to a broad audience interested in the translational field of the application of computational models, such as deep learning, to the study of the brain and the practical applications of neurosurgery. The focus is primarily clinical, and there is a solid foundation of research aspects. With forewords by Michael L.J. Apuzzo and Enrico Coiera, the book is organized into 2 sections: (1) tenets of computational modeling, artificial intelligence, computational analysis, and analysis software; (2) computational neurosurgery applications, including neurodiagnostics, neuro-oncology, vascular neurosurgery, all the neurosurgical disciplines, surgical approaches, intraoperative applications, and ethics and legal aspects.
Deep Learning In Medical Image Analysis And Multimodal Learning For Clinical Decision Support
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Author : M. Jorge Cardoso
language : en
Publisher: Springer
Release Date : 2017-09-07
Deep Learning In Medical Image Analysis And Multimodal Learning For Clinical Decision Support written by M. Jorge Cardoso and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-07 with Computers categories.
This book constitutes the refereed joint proceedings of the Third International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017, and the 6th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017. The 38 full papers presented at DLMIA 2017 and the 5 full papers presented at ML-CDS 2017 were carefully reviewed and selected. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.
Clinical Neurotechnology Meets Artificial Intelligence
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Author : Orsolya Friedrich
language : en
Publisher: Springer Nature
Release Date : 2021-03-03
Clinical Neurotechnology Meets Artificial Intelligence written by Orsolya Friedrich and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-03 with Medical categories.
Neurotechnologies such as brain-computer interfaces (BCIs), which allow technical devices to be used with the power of thought or concentration alone, are no longer a futuristic dream or, depending on the viewpoint, a nightmare. Moreover, the combination of neurotechnologies and AI raises a host of pressing problems. Now that these technologies are about to leave the laboratory and enter the real world, these problems and implications can and should be scrutinized. This volume brings together scholars from a wide range of academic disciplines such as philosophy, law, the social sciences and neurosciences, and is unique in terms of both its focus and its methods. The latter vary considerably, and range from philosophical analysis and phenomenologically inspired descriptions to legal analysis and socio-empirical research. This diversified approach allows the book to explore the entire spectrum of philosophical, normative, legal and empirical dimensions of intelligent neurotechnologies. Philosophical and legal analyses of normative problems are complemented by a thorough empirical assessment of how BCIs and other forms of neurotechnology are being implemented, and what their measurable implications are. To take a closer look at specific neurotechnologies, a number of applications are addressed. Case studies, previously unidentified issues, and normative insights on these cases complement the rich portrait this volume provides. Clinicians, philosophers, lawyers, social scientists and engineers will greatly benefit from the collection of articles compiled in this book, which will likely become a standard reference work on the philosophy of intelligent neurotechnologies.
Neurology And Artificial Intelligence
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Author : KHRITISH SWARGIARY
language : en
Publisher: ERA,US
Release Date : 2025-04-01
Neurology And Artificial Intelligence written by KHRITISH SWARGIARY and has been published by ERA,US this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-01 with Medical categories.
This book is my invitation to you—to marvel at the brain’s wonders, to embrace AI’s promise, and to join me in this journey. I’ve poured my awe, my hopes, and my concerns into these pages, trusting you to carry them forward. Imagine with me a world where a child with epilepsy lives free of fear, where a stroke patient speaks again within hours, where every mind, no matter where it resides, finds care tailored to its needs. But imagine too the shadows we must face—privacy guarded, biases banished, humanity preserved. This is our frontier, yours and mine. Whether you’re a scientist sketching algorithms, a clinician wielding these tools, a student dreaming of discovery, or simply a soul curious about the mind, you have a place here. Explore relentlessly, question bravely, collaborate fiercely. Let’s build a future where technology and compassion are not rivals but allies, where every neuron’s spark lights a path to healing. With all my gratitude and boundless faith in what we can achieve together, Khritish Swargiary (April, 2025)