AIMC Topic: Datasets as Topic

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De-identification of patient notes with recurrent neural networks.

Journal of the American Medical Informatics Association : JAMIA May 1, 2017
OBJECTIVE: Patient notes in electronic health records (EHRs) may contain critical information for medical investigations. However, the vast majority of medical investigators can only access de-identified notes, in order to protect the confidentiality...
Neural Networks, Computer Electronic Health Records Data Anonymization Datasets as Topic Humans
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Protein subcellular localization prediction using multiple kernel learning based support vector machine.

Molecular bioSystems Mar 28, 2017
Predicting the subcellular locations of proteins can provide useful hints that reveal their functions, increase our understanding of the mechanisms of some diseases, and finally aid in the development of novel drugs. As the number of newly discovered...
Intracellular Space Algorithms Reproducibility of Results Computational Biology Datasets as Topic Protein Transport Support Vector Machine Proteins
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Improving CCTA-based lesions' hemodynamic significance assessment by accounting for partial volume modeling in automatic coronary lumen segmentation.

Medical physics Mar 1, 2017
PURPOSE: The goal of this study was to assess the potential added benefit of accounting for partial volume effects (PVE) in an automatic coronary lumen segmentation algorithm that is used to determine the hemodynamic significance of a coronary artery...
Software Retrospective Studies Hemodynamics ROC Curve Humans Machine Learning Datasets as Topic Coronary Vessels Pattern Recognition, Automated Computed Tomography Angiography Imaging, Three-Dimensional Area Under Curve Coronary Angiography Models, Cardiovascular Coronary Stenosis
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MRI-based prostate cancer detection with high-level representation and hierarchical classification.

Medical physics Mar 1, 2017
PURPOSE: Extracting the high-level feature representation by using deep neural networks for detection of prostate cancer, and then based on high-level feature representation constructing hierarchical classification to refine the detection results.
Prostatic Neoplasms Prostate Neural Networks, Computer Humans Image Interpretation, Computer-Assisted Datasets as Topic Sensitivity and Specificity Male Magnetic Resonance Imaging
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Discriminating solitary cysts from soft tissue lesions in mammography using a pretrained deep convolutional neural network.

Medical physics Mar 1, 2017
PURPOSE: It is estimated that 7% of women in the western world will develop palpable breast cysts in their lifetime. Even though cysts have been correlated with risk of developing breast cancer, many of them are benign and do not require follow-up. W...
Diagnosis, Differential Area Under Curve Radiographic Image Interpretation, Computer-Assisted Datasets as Topic Breast Neoplasms ROC Curve Mammography False Positive Reactions Breast Cyst Neural Networks, Computer Humans Female
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Using deep learning to segment breast and fibroglandular tissue in MRI volumes.

Medical physics Feb 1, 2017
PURPOSE: Automated segmentation of breast and fibroglandular tissue (FGT) is required for various computer-aided applications of breast MRI. Traditional image analysis and computer vision techniques, such atlas, template matching, or, edge and surfac...
Pattern Recognition, Automated Female Atlases as Topic Aged Breast Density Skin Adult Artifacts Magnetic Resonance Imaging Datasets as Topic Mammography Middle Aged Humans Image Processing, Computer-Assisted Machine Learning
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Collection of Simulated Data from a Thalamocortical Network Model.

Neuroinformatics Jan 1, 2017
A major challenge in experimental data analysis is the validation of analytical methods in a fully controlled scenario where the justification of the interpretation can be made directly and not just by plausibility. In some sciences, this could be a ...
Neural Networks, Computer Software Computer Simulation Neurons Thalamus Information Dissemination Humans Datasets as Topic Animals Membrane Potentials Cerebral Cortex Models, Neurological Neural Pathways
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Integrated machine learning, molecular docking and 3D-QSAR based approach for identification of potential inhibitors of trypanosomal N-myristoyltransferase.

Molecular bioSystems Nov 15, 2016
N-Myristoyltransferase (NMT) catalyzes the transfer of myristate to the amino-terminal glycine of a subset of proteins, a co-translational modification involved in trafficking substrate proteins to membrane locations, stabilization and protein-protei...
Binding Sites Trypanocidal Agents Acyltransferases Catalytic Domain Parasitic Sensitivity Tests Machine Learning Workflow Algorithms Quantitative Structure-Activity Relationship Molecular Dynamics Simulation Molecular Docking Simulation Enzyme Inhibitors Protein Binding Datasets as Topic
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Can we open the black box of AI?

Nature Oct 6, 2016
Machine Learning Datasets as Topic Robotics Humans Creativity Thinking Neural Networks, Computer Physics Astronomy Uncertainty
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XGSA: A statistical method for cross-species gene set analysis.

Bioinformatics (Oxford, England) Sep 1, 2016
MOTIVATION: Gene set analysis is a powerful tool for determining whether an experimentally derived set of genes is statistically significantly enriched for genes in other pre-defined gene sets, such as known pathways, gene ontology terms, or other ex...
Gene Ontology Regeneration Software Vertebrates Datasets as Topic Conserved Sequence Animals Species Specificity Gene Expression Profiling
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