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Methods and Applications in Neurodegeneration
This Research Topic is part of the Methods and Applications in Frontiers in Neuroscience series. This series aims to highlight the latest experimental techniques and methods used to investigate fundamental questions in neuroscience research, with a major focus on neurodegeneration. Review articles or opinions on methodologies or applications including the advantages and limitations of each are welcome. This Topic includes technologies and up-to-date methods which help advance science. The contributions to this collection will undergo peer-review. Novelty may vary, but the utility of a method or protocol must be evident. We welcome contributions covering all aspects of Neurodegeneration, including xenobiotic and bioagents-induced neurotoxicity as a tool to study neurodegeneration and neuroprotection as well as neurotoxicity models of neurodegeneration. Submissions will be handled by the team of Topic Editors.
Neurogenetics in Neurology: From Molecular Neuroscience to Precision Medicine
This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.
Immunological Challenges Around Pregnancy Complications Associated With Failures of Maternal Tolerance to the Fetus
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Machine Learning on Commodity Tiny Devices
This book aims at the tiny machine learning (TinyML) software and hardware synergy for edge intelligence applications. It presents on-device learning techniques covering model-level neural network design, algorithm-level training optimization, and hardware-level instruction acceleration. Analyzing the limitations of conventional in-cloud computing would reveal that on-device learning is a promising research direction to meet the requirements of edge intelligence applications. As to the cutting-edge research of TinyML, implementing a high-efficiency learning framework and enabling system-level acceleration is one of the most fundamental issues. This book presents a comprehensive discussion of...
Advances in Diagnostics and Treatment of Functional Neurological Disorders: Neurogenomics, Neuromodulation and Machine-Learning
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Experimental and Innovative Approaches to Multi-Target Treatment of Parkinson’s and Alzheimer’s Diseases - Volume I
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