AIMC Topic: Datasets as Topic

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Prediction and functional analysis of prokaryote lysine acetylation site by incorporating six types of features into Chou's general PseAAC.

Journal of theoretical biology Oct 23, 2018
Lysine acetylation is one of the most important types of protein post-translational modifications (PTM) that are widely involved in cellular regulatory processes. To fully understand the regulatory mechanism of acetylation, identification of acetylat...
Computational Biology Support Vector Machine Protein Processing, Post-Translational Bacterial Proteins Datasets as Topic Species Specificity Acetylation Lysine Binding Sites Prokaryotic Cells Bacteria
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Diagnostic accuracy of content-based dermatoscopic image retrieval with deep classification features.

The British journal of dermatology Oct 17, 2018
BACKGROUND: Automated classification of medical images through neural networks can reach high accuracy rates but lacks interpretability.
Humans Retrospective Studies Image Processing, Computer-Assisted Skin Skin Diseases Datasets as Topic Dermoscopy Deep Learning ROC Curve
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Using Deep Learning and Transfer Learning to Accurately Diagnose Early-Onset Glaucoma From Macular Optical Coherence Tomography Images.

American journal of ophthalmology Oct 12, 2018
PURPOSE: We sought to construct and evaluate a deep learning (DL) model to diagnose early glaucoma from spectral-domain optical coherence tomography (OCT) images.
Middle Aged Deep Learning ROC Curve Area Under Curve Sensitivity and Specificity Intraocular Pressure Male Retinal Ganglion Cells Visual Fields Visual Field Tests Transfer, Psychology Tomography, Optical Coherence Datasets as Topic Nerve Fibers Humans Glaucoma Female Reproducibility of Results Aged Adult Glaucoma, Open-Angle Gonioscopy
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Prediction of RNA-protein interactions by combining deep convolutional neural network with feature selection ensemble method.

Journal of theoretical biology Oct 12, 2018
RNA-protein interaction (RPI) plays an important role in the basic cellular processes of organisms. Unfortunately, due to time and cost constraints, it is difficult for biological experiments to determine the relationship between RNA and protein to a...
RNA Datasets as Topic Sequence Analysis Neural Networks, Computer Protein Binding Computational Biology Support Vector Machine
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Use of a Deep Belief Network for Small High-Level Abstraction Data Sets Using Artificial Intelligence with Rule Extraction.

Neural computation Oct 12, 2018
We describe a simple method to transfer from weights in deep neural networks (NNs) trained by a deep belief network (DBN) to weights in a backpropagation NN (BPNN) in the recursive-rule eXtraction (Re-RX) algorithm with J48graft (Re-RX with J48graft)...
Neural Networks, Computer Datasets as Topic Humans
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Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study.

Lancet (London, England) Oct 11, 2018
BACKGROUND: Non-contrast head CT scan is the current standard for initial imaging of patients with head trauma or stroke symptoms. We aimed to develop and validate a set of deep learning algorithms for automated detection of the following key finding...
Trauma Severity Indices Skull Fractures Datasets as Topic Head Intracranial Hemorrhages Deep Learning Brain Injuries Triage Humans Algorithms Retrospective Studies Tomography, X-Ray Computed
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CaSTLe - Classification of single cells by transfer learning: Harnessing the power of publicly available single cell RNA sequencing experiments to annotate new experiments.

PloS one Oct 10, 2018
Single-cell RNA sequencing (scRNA-seq) is an emerging technology for profiling the gene expression of thousands of cells at the single cell resolution. Currently, the labeling of cells in an scRNA-seq dataset is performed by manually characterizing c...
Access to Information Time Factors Datasets as Topic Humans Single-Cell Analysis Retina Pancreas Machine Learning Mice Embryo, Mammalian Hematopoietic Stem Cells Animals Sequence Analysis, RNA
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Development of a deep residual learning algorithm to screen for glaucoma from fundus photography.

Scientific reports Oct 2, 2018
The Purpose of the study was to develop a deep residual learning algorithm to screen for glaucoma from fundus photography and measure its diagnostic performance compared to Residents in Ophthalmology. A training dataset consisted of 1,364 color fundu...
Ophthalmoscopy Photography Fundus Oculi Female Image Interpretation, Computer-Assisted Aged Datasets as Topic Adult Male Humans Middle Aged Glaucoma Deep Learning ROC Curve
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Exploring spatial-frequency-sequential relationships for motor imagery classification with recurrent neural network.

BMC bioinformatics Sep 29, 2018
BACKGROUND: Conventional methods of motor imagery brain computer interfaces (MI-BCIs) suffer from the limited number of samples and simplified features, so as to produce poor performances with spatial-frequency features and shallow classifiers.
Databases, Genetic Humans Neural Networks, Computer Electroencephalography Brain-Computer Interfaces Signal Processing, Computer-Assisted Algorithms Imagination Datasets as Topic Support Vector Machine
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Deep-learning-based, computer-aided classifier developed with a small dataset of clinical images surpasses board-certified dermatologists in skin tumour diagnosis.

The British journal of dermatology Sep 19, 2018
BACKGROUND: Application of deep-learning technology to skin cancer classification can potentially improve the sensitivity and specificity of skin cancer screening, but the number of training images required for such a system is thought to be extremel...
Dermatologists Skin Neoplasms Image Interpretation, Computer-Assisted Dermoscopy Datasets as Topic Sensitivity and Specificity Humans Deep Learning Smartphone Mobile Applications Skin
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