European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology
Apr 27, 2020
Early classification of 2019 novel coronavirus disease (COVID-19) is essential for disease cure and control. Compared with reverse-transcription polymerase chain reaction (RT-PCR), chest computed tomography (CT) imaging may be a significantly more tr...
Purpose; For shoot-through proton treatments, like FLASH radiotherapy, there will be protons exiting the patient which can be used for proton portal imaging (PPI), revealing valuable information for the validation of tumor location in the beam's-eye-...
OBJECTIVE: To determine the diagnostic performance of a deep learning (DL) model in evaluating myometrial invasion (MI) depth on T2-weighted imaging (T2WI)-based endometrial cancer (EC) MR imaging (ECM).
PURPOSE: To develop an objective and automated method for measuring intraocular pressure using deep learning and fixed-force Goldmann applanation tonometry (GAT) techniques.
PURPOSE: Natural language processing (NLP) can be used for automatic flagging of radiology reports. We assessed deep learning models for classifying non-English head CT reports.
OBJECTIVES: The evaluation of lymph node (LN) status by radiologists based on preoperative computed tomography (CT) lacks high precision for early lung cancer patients; erroneous evaluations result in inappropriate therapeutic plans and increase the ...
A proper echocardiographic study requires several video clips recorded from different acquisition angles for observation of the complex cardiac anatomy. However, these video clips are not necessarily labeled in a database. Identification of the acqui...
Neural networks : the official journal of the International Neural Network Society
Apr 24, 2020
The accuracy of deep learning (e.g., convolutional neural networks) for an image classification task critically relies on the amount of labeled training data. Aiming to solve an image classification task on a new domain that lacks labeled data but ga...
Journal of chemical information and modeling
Apr 24, 2020
Advances in deep neural network (DNN)-based molecular property prediction have recently led to the development of models of remarkable accuracy and generalization ability, with graph convolutional neural networks (GCNNs) reporting state-of-the-art pe...
PURPOSE: In this work we develop and validate a fully automated postprocessing framework for in vivo diffusion tensor cardiac magnetic resonance (DT-CMR) data powered by deep learning.
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