Neuroimaging clinics of North America
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Neuroimaging Clin. N. Am. · Nov 2020
ReviewAn East Coast Perspective on Artificial Intelligence and Machine Learning: Part 1: Hemorrhagic Stroke Imaging and Triage.
Hemorrhagic stroke is a medical emergency. Artificial intelligence techniques and algorithms may be used to automatically detect and quantitate intracranial hemorrhage in a semiautomated fashion. ⋯ This article reviews artificial intelligence algorithms for intracranial hemorrhage detection, quantification, and prognostication. Multiple algorithms currently being explored are described and illustrated with the help of examples.
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Neuroimaging Clin. N. Am. · Nov 2020
ReviewOverview of Machine Learning: Part 2: Deep Learning for Medical Image Analysis.
Deep learning has contributed to solving complex problems in science and engineering. This article provides the fundamental background required to understand and develop deep learning models for medical imaging applications. The authors review the main deep learning architectures such as multilayer perceptron, convolutional neural networks, autoencoders, recurrent neural networks, and generative adversarial neural networks. They also discuss the strategies for training deep learning models when the available datasets are imbalanced or of limited size and conclude with a discussion of the obstacles and challenges hindering the deployment of deep learning solutions in clinical settings.
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Natural language processing (NLP) is an interdisciplinary field, combining linguistics, computer science, and artificial intelligence to enable machines to read and understand human language for meaningful purposes. Recent advancements in deep learning have begun to offer significant improvements in NLP task performance. These techniques have the potential to create new automated tools that could improve clinical workflows and unlock unstructured textual information contained in radiology and clinical reports for the development of radiology and clinical artificial intelligence applications. These applications will combine the appropriate application of classic linguistic and NLP preprocessing techniques, modern NLP techniques, and modern deep learning techniques.
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Neuroimaging Clin. N. Am. · Nov 2020
ReviewAn East Coast Perspective on Artificial Intelligence and Machine Learning: Part 2: Ischemic Stroke Imaging and Triage.
Acute ischemic stroke constitutes approximately 85% of strokes. Most strokes occur in community settings; thus, automatic algorithms techniques are attractive for managing these cases. ⋯ This article reviews algorithms for artificial intelligence techniques that may be used to detect and localize acute ischemic stroke. We describe artificial intelligence algorithms for these tasks and illustrate them with examples.