AIMC Topic: Sensitivity and Specificity

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Orthogonal convolutional neural networks for automatic sleep stage classification based on single-channel EEG.

Computer methods and programs in biomedicine Sep 27, 2019
BACKGROUND AND OBJECTIVE: In recent years, several automatic sleep stage classification methods based on convolutional neural networks (CNN) by learning hierarchical feature representation automatically from raw EEG data have been proposed. However, ...
Sleep Stages Databases, Factual Humans Reproducibility of Results Neural Networks, Computer Sleep Apnea, Obstructive Adult Machine Learning Sensitivity and Specificity Sleep Algorithms Male Calibration Polysomnography Time Factors Sleep Wake Disorders Electrocardiography Electroencephalography Signal Processing, Computer-Assisted
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An overview and metanalysis of machine and deep learning-based CRISPR gRNA design tools.

RNA biology Sep 27, 2019
The CRISPR-Cas9 system has become the most promising and versatile tool for genetic manipulation applications. Albeit the technology has been broadly adopted by both academic and pharmaceutic societies, the activity (on-target) and specificity (off-t...
Deep Learning Humans CRISPR-Cas Systems Machine Learning Algorithms Gene Editing Sensitivity and Specificity Gene Targeting RNA, Guide, CRISPR-Cas Systems
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Artificial intelligence in computer-aided diagnosis of abdomen diseases.

Science China. Life sciences Sep 27, 2019
Abdomen Diagnostic Imaging Gastrointestinal Diseases Neural Networks, Computer Humans Artificial Intelligence Sensitivity and Specificity Diagnosis, Computer-Assisted Biosensing Techniques
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Keratoconus detection using deep learning of colour-coded maps with anterior segment optical coherence tomography: a diagnostic accuracy study.

BMJ open Sep 27, 2019
OBJECTIVE: To evaluate the diagnostic accuracy of keratoconus using deep learning of the colour-coded maps measured with the swept-source anterior segment optical coherence tomography (AS-OCT).
Humans Retrospective Studies Sensitivity and Specificity Disease Progression Case-Control Studies Deep Learning Keratoconus Tomography, Optical Coherence
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Deep learning-enabled system for rapid pneumothorax screening on chest CT.

European journal of radiology Sep 26, 2019
PURPOSE: Prompt diagnosis and quantitation of pneumothorax impact decisions pertaining to patient management. The purpose of our study was to develop and evaluate the accuracy of a deep learning (DL)-based image classification program for detection o...
Radiography, Thoracic Female Reproducibility of Results Time Aged Pneumothorax Deep Learning Aged, 80 and over Adult Young Adult Humans Adolescent Sensitivity and Specificity Neural Networks, Computer Child, Preschool Male Tomography, X-Ray Computed Child Middle Aged Support Vector Machine
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Seizure Prediction in Scalp EEG Using 3D Convolutional Neural Networks With an Image-Based Approach.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 25, 2019
Epileptic seizures occur as a result of a process that develops over time and space in epileptic networks. In this study, we aim at developing a generalizable method for patient-specific seizure prediction by evaluating the spatio-temporal correlatio...
False Positive Reactions Scalp Adolescent Child, Preschool Child Image Processing, Computer-Assisted Poisson Distribution Predictive Value of Tests Color Electroencephalography Humans Seizures Algorithms Neural Networks, Computer Adult Sensitivity and Specificity Male Infant
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Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs.

Ophthalmology Sep 24, 2019
PURPOSE: To develop and validate a deep learning (DL) algorithm that predicts referable glaucomatous optic neuropathy (GON) and optic nerve head (ONH) features from color fundus images, to determine the relative importance of these features in referr...
Ophthalmologists Glaucoma, Open-Angle Specialization Deep Learning ROC Curve Area Under Curve Referral and Consultation Datasets as Topic Nerve Fibers Optic Disk Retinal Ganglion Cells Optic Nerve Diseases Female Aged Sensitivity and Specificity Male Middle Aged Humans Retrospective Studies
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Using machine learning to understand neuromorphological change and image-based biomarker identification in Cavalier King Charles Spaniels with Chiari-like malformation-associated pain and syringomyelia.

Journal of veterinary internal medicine Sep 24, 2019
BACKGROUND: Chiari-like malformation (CM) is a complex malformation of the skull and cranial cervical vertebrae that potentially results in pain and secondary syringomyelia (SM). Chiari-like malformation-associated pain (CM-P) can be challenging to d...
Biomarkers Retrospective Studies Female Sensitivity and Specificity Animals Machine Learning Dog Diseases Pain Arnold-Chiari Malformation Syringomyelia Male ROC Curve Area Under Curve Dogs
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Detection of Hemodynamically Significant Coronary Stenosis: CT Myocardial Perfusion versus Machine Learning CT Fractional Flow Reserve.

Radiology Sep 24, 2019
Background Direct intraindividual comparison of dynamic CT myocardial perfusion imaging (MPI) and machine learning (ML)-based CT fractional flow reserve (FFR) has not been explored for diagnosing hemodynamically significant coronary artery disease. P...
Humans Middle Aged Severity of Illness Index Hemodynamics ROC Curve Aged Coronary Angiography Aged, 80 and over Machine Learning Radiographic Image Interpretation, Computer-Assisted Adult Prospective Studies Computed Tomography Angiography Sensitivity and Specificity Tomography, X-Ray Computed Coronary Stenosis Male Female Fractional Flow Reserve, Myocardial
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Sensitivity Analysis and Extensions of Testing the Causal Direction of Dependence: A Rejoinder to Thoemmes (2019).

Multivariate behavioral research Sep 23, 2019
A commentary by Thoemmes on Wiedermann and Sebastian's introductory article on Direction Dependence Analysis (DDA) is responded to in the interest of elaborating and extending direction dependence principles to evaluate causal effect directionality. ...
Causality Models, Statistical Psychology Linear Models Models, Econometric Humans Machine Learning Sensitivity and Specificity Models, Theoretical
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