AIMC Topic:
Databases, Factual

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Fast and fully-automated detection and segmentation of pulmonary nodules in thoracic CT scans using deep convolutional neural networks.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Mar 22, 2019
Deep learning techniques have been extensively used in computerized pulmonary nodule analysis in recent years. Many reported studies still utilized hybrid methods for diagnosis, in which convolutional neural networks (CNNs) are used only as one part ...
Lung Neoplasms Radiographic Image Interpretation, Computer-Assisted Female Male Diagnosis, Computer-Assisted Deep Learning Neural Networks, Computer Databases, Factual Tomography, X-Ray Computed Humans
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A Novel Weakly Supervised Multitask Architecture for Retinal Lesions Segmentation on Fundus Images.

IEEE transactions on medical imaging Mar 20, 2019
Obtaining the complete segmentation map of retinal lesions is the first step toward an automated diagnosis tool for retinopathy that is interpretable in its decision-making. However, the limited availability of ground truth lesion detection maps at a...
Humans Databases, Factual ROC Curve Fundus Oculi Retina Diagnostic Techniques, Ophthalmological Supervised Machine Learning Image Interpretation, Computer-Assisted Retinal Diseases
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CNNs for automatic glaucoma assessment using fundus images: an extensive validation.

Biomedical engineering online Mar 20, 2019
BACKGROUND: Most current algorithms for automatic glaucoma assessment using fundus images rely on handcrafted features based on segmentation, which are affected by the performance of the chosen segmentation method and the extracted features. Among ot...
Databases, Factual Time Factors Image Processing, Computer-Assisted Fundus Oculi Humans Neural Networks, Computer Glaucoma
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Distinction between benign and malignant breast masses at breast ultrasound using deep learning method with convolutional neural network.

Japanese journal of radiology Mar 19, 2019
PURPOSE: We aimed to use deep learning with convolutional neural network (CNN) to discriminate between benign and malignant breast mass images from ultrasound.
Aged, 80 and over Young Adult Adult Sensitivity and Specificity Female Reproducibility of Results Aged ROC Curve Diagnosis, Differential Ultrasonography, Mammary Breast Breast Neoplasms Middle Aged Deep Learning Humans Neural Networks, Computer Databases, Factual Retrospective Studies Image Interpretation, Computer-Assisted
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MTBI Identification From Diffusion MR Images Using Bag of Adversarial Visual Features.

IEEE transactions on medical imaging Mar 18, 2019
In this paper, we propose bag of adversarial features (BAFs) for identifying mild traumatic brain injury (MTBI) patients from their diffusion magnetic resonance images (MRIs) (obtained within one month of injury) by incorporating unsupervised feature...
Image Interpretation, Computer-Assisted Brain Concussion Diffusion Magnetic Resonance Imaging Middle Aged Deep Learning Adolescent ROC Curve Brain Young Adult Adult Humans Algorithms Databases, Factual
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Contemporary pharmacogenetic assays in view of the PharmGKB database.

Pharmacogenomics Mar 18, 2019
AIM: Six modern PGx assays were compared with the Pharmacogenomics Knowledge Base (PharmGKB) to determine the proportion of the currently known PGx genotypes that are assessed by these assays.
Pharmacogenetics Genotype Humans Knowledge Bases Databases, Factual Pharmacogenomic Testing
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Machine learning to predict occult nodal metastasis in early oral squamous cell carcinoma.

Oral oncology Mar 16, 2019
OBJECTIVES: To develop and validate an algorithm to predict occult nodal metastasis in clinically node negative oral cavity squamous cell carcinoma (OCSCC) using machine learning. To compare algorithm performance to a model based on tumor depth of in...
Carcinoma, Squamous Cell Aged Humans Lymphatic Metastasis Sensitivity and Specificity Artificial Intelligence Middle Aged Databases, Factual Male Neoplasm Grading Machine Learning ROC Curve Prognosis Mouth Neoplasms Algorithms Female Models, Theoretical
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A Generic Human-Machine Annotation Framework Based on Dynamic Cooperative Learning.

IEEE transactions on cybernetics Mar 14, 2019
The task of obtaining meaningful annotations is a tedious work, incurring considerable costs and time consumption. Dynamic active learning and cooperative learning are recently proposed approaches to reduce human effort of annotating data with subjec...
Data Curation Man-Machine Systems Male Middle Aged Supervised Machine Learning Humans Algorithms Databases, Factual Female Reproducibility of Results Young Adult Adult
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Financial time series forecasting using twin support vector regression.

PloS one Mar 13, 2019
Financial time series forecasting is a crucial measure for improving and making more robust financial decisions throughout the world. Noisy data and non-stationarity information are the two key factors in financial time series prediction. This paper ...
Models, Economic Time Factors Humans Support Vector Machine Investments Forecasting Regression Analysis Decision Making, Computer-Assisted Databases, Factual Financial Management
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Dynamic MRI using model-based deep learning and SToRM priors: MoDL-SToRM.

Magnetic resonance in medicine Mar 12, 2019
PURPOSE: To introduce a novel framework to combine deep-learned priors along with complementary image regularization penalties to reconstruct free breathing & ungated cardiac MRI data from highly undersampled multi-channel measurements.
Humans Algorithms Magnetic Resonance Imaging Heart Respiration Cardiac Imaging Techniques Databases, Factual Deep Learning Image Processing, Computer-Assisted
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