Results 61 to 70 of about 1,925,096 (328)
IEEE Access, 2020 In this paper, ultrasound imaging of benign and malignant thyroid nodules to predict the depth of the learning algorithm, built on circulation volume product thyroid ultrasound image neural network forecasting model.
Yinghui Lu, Yi Yang, Wan Chen
doaj +1 more source
Sequential Convolutional Recurrent Neural Networks for Fast Automatic Modulation Classification
IEEE Access, 2021 A novel and efficient end-to-end learning model for automatic modulation classification is proposed for wireless spectrum monitoring applications, which automatically learns from the time domain in-phase and quadrature data without requiring the design ...
Kaisheng Liao +4 more
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah +7 more
wiley +1 more source
Adverse Drug Reaction Classification With Deep Neural Networks [PDF]
, 2016 We study the problem of detecting sentences describing adverse drug reactions (ADRs) and frame the problem as binary classification. We investigate different neural network (NN) architectures for ADR classification.
He, Yulan +3 more
core +1 more source
, 2017 Lung nodule classification is a class imbalanced problem, as nodules are found with much lower frequency than non-nodules. In the class imbalanced problem, conventional classifiers tend to be overwhelmed by the majority class and ignore the minority ...
Nakano, Hiroki +3 more
core +1 more source
Functional and Structural Evidence of Neurofluid Circuit Aberrations in Huntington Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Disrupted neurofluid regulation may contribute to neurodegeneration in Huntington disease (HD). Because neurofluid pathways influence waste clearance, inflammation, and the distribution of central nervous system (CNS)–delivered therapeutics, understanding their dysfunction is increasingly important as targeted treatments emerge.
Kilian Hett +8 more
wiley +1 more source
Research onconvolutional neural network for reservoir parameter prediction
Tongxin xuebao, 2016 As the branch of artificial intelligence,artificial neural network solved many difficult practical problems in pattern recognition and classification prediction field successfully.However,they cannot learn the feature from networks.In recent years,deep ...
You-xiang DUAN, Gen-tian LI, Qi-feng SUN
doaj +2 more sources
SMT Assembly Inspection Using Dual-Stream Convolutional Networks and Two Solder Regions
Applied Sciences, 2020 The automated optical inspection of a surface mount technology line inspects a printed circuit board for quality assurance, and subsequently classifies the chip assembly defects.
Young-Gyu Kim, Tae-Hyoung Park
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Lithosphere, 2021 Average pore pressure in oil formation is an important parameter to measure energy in the formation and the capacity of injection–production. In past studies, average pore pressure mainly depends on pressure build-up test results, which have a high cost ...
Chaoyang Hu +4 more
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Advanced Engineering Materials, EarlyView.This article provides an overview of recent advancements in bulk processing of rare‐earth‐free hard magnetic materials. It also addresses related simulation approaches at different scales. The research on rare‐earth‐free magnetic materials has increased significantly in recent years, driven by supply chain issues, environmental and social concerns, and
Daniel Scheiber, Andrea Bachmaier
wiley +1 more source