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: deep learning-based radiomics for the time-to-event outcome prediction in lung cancer.
Scientific reports
Jul 23, 2020
Hand-crafted radiomics has been used for developing models in order to predict time-to-event clinical outcomes in patients with lung cancer. Hand-crafted features, however, are pre-defined and extracted without taking the desired target into account....
BiPOm: a rule-based ontology to represent and infer molecule knowledge from a biological process-centered viewpoint.
BMC bioinformatics
Jul 23, 2020
BACKGROUND: Managing and organizing biological knowledge remains a major challenge, due to the complexity of living systems. Recently, systemic representations have been promising in tackling such a challenge at the whole-cell scale. In such represen...
ECG Biometrics Using Deep Learning and Relative Score Threshold Classification.
Sensors (Basel, Switzerland)
Jul 22, 2020
The field of biometrics is a pattern recognition problem, where the individual traits are coded, registered, and compared with other database records. Due to the difficulties in reproducing Electrocardiograms (ECG), their usage has been emerging in t...
Using deep learning to predict the hand-foot-and-mouth disease of enterovirus A71 subtype in Beijing from 2011 to 2018.
Scientific reports
Jul 22, 2020
Hand-foot-and-month disease (HFMD), especially the enterovirus A71 (EV-A71) subtype, is a major health problem in Beijing, China. Previous studies mainly used regressive models to forecast the prevalence of HFMD, ignoring its intrinsic age groups. Th...
Spatial-Frequency Feature Learning and Classification of Motor Imagery EEG Based on Deep Convolution Neural Network.
Computational and mathematical methods in medicine
Jul 20, 2020
EEG pattern recognition is an important part of motor imagery- (MI-) based brain computer interface (BCI) system. Traditional EEG pattern recognition algorithm usually includes two steps, namely, feature extraction and feature classification. In feat...
Multi-class motor imagery EEG classification using collaborative representation-based semi-supervised extreme learning machine.
Medical & biological engineering & computing
Jul 16, 2020
Both labeled and unlabeled data have been widely used in electroencephalographic (EEG)-based brain-computer interface (BCI). However, labeled EEG samples are generally scarce and expensive to collect, while unlabeled samples are considered to be abun...
α-Satellite: An AI-Driven System and Benchmark Datasets for Dynamic COVID-19 Risk Assessment in the United States.
IEEE journal of biomedical and health informatics
Jul 15, 2020
The fast evolving and deadly outbreak of coronavirus disease (COVID-19) has posed grand challenges to human society. To slow the spread of virus infections and better respond for community mitigation, by advancing capabilities of artificial intellige...
Feature fusion via Deep Random Forest for facial age estimation.
Neural networks : the official journal of the International Neural Network Society
Jul 14, 2020
In the last few years, human age estimation from face images attracted the attention of many researchers in computer vision and machine learning fields. This is due to its numerous applications. In this paper, we propose a new architecture for age es...
An Intelligent Diagnosis Method of Brain MRI Tumor Segmentation Using Deep Convolutional Neural Network and SVM Algorithm.
Computational and mathematical methods in medicine
Jul 14, 2020
Among the currently proposed brain segmentation methods, brain tumor segmentation methods based on traditional image processing and machine learning are not ideal enough. Therefore, deep learning-based brain segmentation methods are widely used. In t...
Fast interactive medical image segmentation with weakly supervised deep learning method.
International journal of computer assisted radiology and surgery
Jul 11, 2020
PURPOSE: To achieve accurate image segmentation, which is the first critical step in medical image analysis and interventions, using deep neural networks seems a promising approach provided sufficiently large and diverse annotated data from experts. ...
Reproducibility of Results
Male
Echocardiography
Diagnosis, Computer-Assisted
Neural Networks, Computer
Humans
Databases, Factual
Prostate
Tomography, X-Ray Computed
Observer Variation
Deep Learning
Pattern Recognition, Automated
Ultrasonography
Brachytherapy
Image Processing, Computer-Assisted
Prostatic Neoplasms
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