AIMC Topic: ROC Curve

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Deep learning meets ontologies: experiments to anchor the cardiovascular disease ontology in the biomedical literature.

Journal of biomedical semantics Apr 12, 2018
BACKGROUND: Automatic identification of term variants or acceptable alternative free-text terms for gene and protein names from the millions of biomedical publications is a challenging task. Ontologies, such as the Cardiovascular Disease Ontology (CV...
Humans Cardiovascular Diseases Deep Learning ROC Curve PubMed Biological Ontologies Molecular Sequence Annotation
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An Automatic Diagnosis Method of Facial Acne Vulgaris Based on Convolutional Neural Network.

Scientific reports Apr 11, 2018
In this paper, we present a new automatic diagnosis method for facial acne vulgaris which is based on convolutional neural networks (CNNs). To overcome the shortcomings of previous methods which were the inability to classify enough types of acne vul...
Acne Vulgaris Photography Skin Image Interpretation, Computer-Assisted Datasets as Topic Face Neural Networks, Computer Prospective Studies ROC Curve Humans
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Automated detection of focal cortical dysplasia type II with surface-based magnetic resonance imaging postprocessing and machine learning.

Epilepsia Apr 10, 2018
OBJECTIVE: Focal cortical dysplasia (FCD) is a major pathology in patients undergoing surgical resection to treat pharmacoresistant epilepsy. Magnetic resonance imaging (MRI) postprocessing methods may provide essential help for detection of FCD. In ...
Female Young Adult Adult Sensitivity and Specificity Humans Machine Learning Brain Child ROC Curve Magnetic Resonance Imaging Area Under Curve Male Middle Aged Adolescent Child, Preschool Epilepsy Neuroimaging Malformations of Cortical Development, Group I
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Application of Deep Learning Architectures for Accurate and Rapid Detection of Internal Mechanical Damage of Blueberry Using Hyperspectral Transmittance Data.

Sensors (Basel, Switzerland) Apr 7, 2018
Deep learning has become a widely used powerful tool in many research fields, although not much so yet in agriculture technologies. In this work, two deep convolutional neural networks (CNN), viz. Residual Network (ResNet) and its improved version na...
Neural Networks, Computer Machine Learning Algorithms Time Factors ROC Curve Blueberry Plants
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Novel forecasting approaches using combination of machine learning and statistical models for flood susceptibility mapping.

Journal of environmental management Apr 5, 2018
In this research, eight individual machine learning and statistical models are implemented and compared, and based on their results, seven ensemble models for flood susceptibility assessment are introduced. The individual models included artificial n...
ROC Curve Models, Statistical Machine Learning Iran Forecasting Floods
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Transcriptomics and machine learning predict diagnosis and severity of growth hormone deficiency.

JCI insight Apr 5, 2018
BACKGROUND: The effect of gene expression data on diagnosis remains limited. Here, we show how diagnosis and classification of growth hormone deficiency (GHD) can be achieved from a single blood sample using a combination of transcriptomics and rando...
Gene Regulatory Networks Polymorphism, Single Nucleotide Predictive Value of Tests Principal Component Analysis Child, Preschool Child ROC Curve Healthy Volunteers Datasets as Topic Humans Machine Learning Biomarkers Female Case-Control Studies Adolescent Human Growth Hormone Growth Disorders Male Severity of Illness Index Gene Expression Profiling Transcriptome
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A hidden Markov tree model for testing multiple hypotheses corresponding to Gene Ontology gene sets.

BMC bioinformatics Mar 27, 2018
BACKGROUND: Testing predefined gene categories has become a common practice for scientists analyzing high throughput transcriptome data. A systematic way of testing gene categories leads to testing hundreds of null hypotheses that correspond to nodes...
Bayes Theorem Markov Chains Gene Ontology Transcriptome Humans Quantitative Trait Loci ROC Curve Algorithms Models, Genetic Computer Simulation Models, Theoretical
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Completing sparse and disconnected protein-protein network by deep learning.

BMC bioinformatics Mar 22, 2018
BACKGROUND: Protein-protein interaction (PPI) prediction remains a central task in systems biology to achieve a better and holistic understanding of cellular and intracellular processes. Recently, an increasing number of computational methods have sh...
Area Under Curve ROC Curve Bayes Theorem Humans Protein Interaction Maps Saccharomyces cerevisiae Neural Networks, Computer Proteins Machine Learning Algorithms
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Detecting and classifying lesions in mammograms with Deep Learning.

Scientific reports Mar 15, 2018
In the last two decades, Computer Aided Detection (CAD) systems were developed to help radiologists analyse screening mammograms, however benefits of current CAD technologies appear to be contradictory, therefore they should be improved to be ultimat...
Humans Breast Neoplasms Data Accuracy Neural Networks, Computer Diagnosis, Computer-Assisted Mass Screening Machine Learning Deep Learning Early Detection of Cancer Databases, Factual ROC Curve Mammography Female
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Prediction of cardiac death after adenosine myocardial perfusion SPECT based on machine learning.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology Mar 14, 2018
BACKGROUND: We developed machine-learning (ML) models to estimate a patient's risk of cardiac death based on adenosine myocardial perfusion SPECT (MPS) and associated clinical data, and compared their performance to baseline logistic regression (LR)....
Female Reproducibility of Results Aged Male Middle Aged ROC Curve Support Vector Machine Follow-Up Studies Humans Probability Machine Learning Regression Analysis Risk Algorithms Area Under Curve Tomography, Emission-Computed, Single-Photon Heart Death, Sudden, Cardiac
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