We propose a novel dual-domain convolutional neural network framework to improve structural information of routine 3 T images. We introduce a parameter-efficient butterfly network that involves two complementary domains: a spatial domain and a freque...
PURPOSE: To develop and evaluate a novel deep learning-based reconstruction framework called SANTIS (Sampling-Augmented Neural neTwork with Incoherent Structure) for efficient MR image reconstruction with improved robustness against sampling pattern ...
International journal of medical informatics
Jun 5, 2019
BACKGROUND: This work deals with Natural Language Processing applied to the clinical domain. Specifically, the work deals with a Medical Entity Recognition (MER) on Electronic Health Records (EHRs). Developing a MER system entailed heavy data preproc...
Biomedical events play a key role in improving biomedical research. Event trigger identification, extracting the words describing the event types, is a crucial and prerequisite step in the pipeline process of biomedical event extraction. There exist ...
PURPOSE: Scatter is a major factor degrading the image quality of cone beam computed tomography (CBCT). Conventional scatter correction strategies require handcrafted analytical models with ad hoc assumptions, which often leads to less accurate scatt...
IMPORTANCE: Duodenal biopsies from children with enteropathies associated with undernutrition, such as environmental enteropathy (EE) and celiac disease (CD), display significant histopathological overlap.
The classification of electrocardiograms (ECG) plays an important role in the clinical diagnosis of heart disease. This paper proposes an effective system development and implementation for ECG classification based on faster regions with a convolutio...
Annals of the New York Academy of Sciences
Jun 4, 2019
Discovering the true nature of reality may ultimately hinge on grasping the nature and essence of human understanding. What are the fundamental elements or building blocks of human cognition? And how will the rise of superintelligent machines challen...
Neural networks : the official journal of the International Neural Network Society
Jun 4, 2019
We seek to (i) characterize the learning architectures exploited in biological neural networks for training on very few samples, and (ii) port these algorithmic structures to a machine learning context. The moth olfactory network is among the simples...
Computer methods and programs in biomedicine
Jun 4, 2019
BACKGROUND AND OBJECTIVE: Risk prediction models aim at identifying people at higher risk of developing a target disease. Feature selection is particularly important to improve the prediction model performance avoiding overfitting and to identify the...
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