AIMC Topic:
Databases, Factual
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Photomontage detection using steganography technique based on a neural network.
Neural networks : the official journal of the International Neural Network Society
Apr 17, 2019
This article presents a steganographic method StegoNN based on neural networks. The method is able to identify a photomontage from presented signed images. Unlike other academic approaches using neural networks primarily as classifiers, the StegoNN m...
Deep Q Learning Driven CT Pancreas Segmentation With Geometry-Aware U-Net.
IEEE transactions on medical imaging
Apr 16, 2019
The segmentation of pancreas is important for medical image analysis, yet it faces great challenges of class imbalance, background distractions, and non-rigid geometrical features. To address these difficulties, we introduce a deep Q network (DQN) dr...
A machine learning approach to knee osteoarthritis phenotyping: data from the FNIH Biomarkers Consortium.
Osteoarthritis and cartilage
Apr 16, 2019
OBJECTIVE: Knee osteoarthritis (KOA) is a heterogeneous condition representing a variety of potentially distinct phenotypes. The purpose of this study was to apply innovative machine learning approaches to KOA phenotyping in order to define progressi...
Congresses as Topic
National Institutes of Health (U.S.)
Biological Variation, Population
Collagen Type II
Cartilage, Articular
Menisci, Tibial
United States
Pain Measurement
Osteoarthritis, Knee
Biomarkers
Female
Humans
Aged
Machine Learning
Disease Progression
Databases, Factual
Severity of Illness Index
Male
Middle Aged
Significance of Softmax-Based Features in Comparison to Distance Metric Learning-Based Features.
IEEE transactions on pattern analysis and machine intelligence
Apr 15, 2019
End-to-end distance metric learning (DML) has been applied to obtain features useful in many computer vision tasks. However, these DML studies have not provided equitable comparisons between features extracted from DML-based networks and softmax-base...
Approximating the Ideal Observer and Hotelling Observer for Binary Signal Detection Tasks by Use of Supervised Learning Methods.
IEEE transactions on medical imaging
Apr 15, 2019
It is widely accepted that the optimization of medical imaging system performance should be guided by task-based measures of image quality (IQ). Task-based measures of IQ quantify the ability of an observer to perform a specific task, such as detecti...
ECG Multilead Interval Estimation Using Support Vector Machines.
Journal of healthcare engineering
Apr 15, 2019
This work reports a multilead interval measurement algorithm for a high-resolution digital electrocardiograph. The software enables off-line ECG processing including detection as well as an accurate multilead interval detection algorithm using sup...
Dense networks with relative location awareness for thorax disease identification.
Medical physics
Apr 14, 2019
PURPOSE: Chest X-ray is one of the most common examinations for diagnosing heart and lung diseases. Due to the existing of a large number of clinical cases, many automated diagnosis algorithms based on chest X-ray images have been proposed. To our kn...
Predicting daily outcomes in acetaminophen-induced acute liver failure patients with machine learning techniques.
Computer methods and programs in biomedicine
Apr 11, 2019
BACKGROUND/OBJECTIVE: Assessing prognosis for acetaminophen-induced acute liver failure (APAP-ALF) patients during the first week of hospitalization often presents significant challenges. Current models such as the King's College Criteria (KCC) and t...
Bayes Theorem
Registries
Linear Models
Acetaminophen
Humans
Liver Failure, Acute
Female
Machine Learning
Adult
Treatment Outcome
Predictive Value of Tests
Sensitivity and Specificity
Middle Aged
Databases, Factual
Area Under Curve
Male
Severity of Illness Index
ROC Curve
Prognosis
Retrospective Studies
Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment.
PloS one
Apr 10, 2019
An image classification algorithm based on adaptive feature weight updating is proposed to address the low classification accuracy of the current single-feature classification algorithms and simple multifeature fusion algorithms. The MapReduce parall...
[Can Big Data change our practices?].
Journal francais d'ophtalmologie
Apr 9, 2019
The European Medicines Agency has defined Big Data by the "3 V's": Volume, Velocity and Variety. These large databases allow access to real life data on patient care. They are particularly suited for studies of adverse events and pharmacoepidemiology...
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