AIMC Topic: Sensitivity and Specificity

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Classification of Aortic Dissection and Rupture on Post-contrast CT Images Using a Convolutional Neural Network.

Journal of digital imaging Dec 1, 2019
Aortic dissections and ruptures are life-threatening injuries that must be immediately treated. Our national radiology practice receives dozens of these cases each month, but no automated process is currently available to check for critical pathologi...
Aortic Rupture Radiographic Image Interpretation, Computer-Assisted Aortic Dissection Neural Networks, Computer Aorta Prospective Studies Tomography, X-Ray Computed Radiographic Image Enhancement Humans Female Sensitivity and Specificity Reproducibility of Results Male Middle Aged Contrast Media
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Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs.

JAMA ophthalmology Dec 1, 2019
IMPORTANCE: A deep learning system (DLS) that could automatically detect glaucomatous optic neuropathy (GON) with high sensitivity and specificity could expedite screening for GON.
Humans Databases, Factual Female Male Deep Learning ROC Curve Sensitivity and Specificity Cross-Sectional Studies False Positive Reactions Diagnostic Techniques, Ophthalmological Photography Predictive Value of Tests Glaucoma, Open-Angle Area Under Curve Fundus Oculi Optic Nerve Diseases
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Evaluation of a Deep Learning System For Identifying Glaucomatous Optic Neuropathy Based on Color Fundus Photographs.

Journal of glaucoma Dec 1, 2019
PRECIS: Pegasus outperformed 5 of the 6 ophthalmologists in terms of diagnostic performance, and there was no statistically significant difference between the deep learning system and the "best case" consensus between the ophthalmologists. The agreem...
Photography Ophthalmologists Glaucoma, Open-Angle Observer Variation Optic Disk Optic Nerve Diseases Diagnostic Techniques, Ophthalmological Diagnosis, Computer-Assisted Deep Learning ROC Curve Humans Area Under Curve Retrospective Studies Female Intraocular Pressure Aged Adult Male Sensitivity and Specificity Middle Aged
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Computer-Aided Diagnosis (CAD) of Pulmonary Nodule of Thoracic CT Image Using Transfer Learning.

Journal of digital imaging Dec 1, 2019
Computer-aided diagnosis (CAD) has already been widely used in medical image processing. We recently make another trial to implement convolutional neural network (CNN) on the classification of pulmonary nodules of thoracic CT images. The biggest chal...
Radiographic Image Interpretation, Computer-Assisted Lung Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Humans Tomography, X-Ray Computed Reproducibility of Results Sensitivity and Specificity Machine Learning Databases, Factual
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Deep Learning Method for Automated Classification of Anteroposterior and Posteroanterior Chest Radiographs.

Journal of digital imaging Dec 1, 2019
Ensuring correct radiograph view labeling is important for machine learning algorithm development and quality control of studies obtained from multiple facilities. The purpose of this study was to develop and test the performance of a deep convolutio...
Humans Databases, Factual Retrospective Studies Child Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic Reproducibility of Results Adult Sensitivity and Specificity Deep Learning
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Deep Learning for Detection of Complete Anterior Cruciate Ligament Tear.

Journal of digital imaging Dec 1, 2019
Deep learning for MRI detection of sports injuries poses unique challenges. To address these difficulties, this study examines the feasibility and incremental benefit of several customized network architectures in evaluation of complete anterior cruc...
Humans Retrospective Studies Magnetic Resonance Imaging Knee Joint Image Interpretation, Computer-Assisted Anterior Cruciate Ligament Injuries Anterior Cruciate Ligament Athletic Injuries Sensitivity and Specificity Female Male Reproducibility of Results Deep Learning Young Adult Adolescent Adult
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OPTICAL COHERENCE TOMOGRAPHY BIOMARKERS TO DISTINGUISH DIABETIC MACULAR EDEMA FROM PSEUDOPHAKIC CYSTOID MACULAR EDEMA USING MACHINE LEARNING ALGORITHMS.

Retina (Philadelphia, Pa.) Dec 1, 2019
PURPOSE: In diabetic patients presenting with macular edema (ME) shortly after cataract surgery, identifying the underlying pathology can be challenging and influence management. Our aim was to develop a simple clinical classifier able to confirm a d...
Aged Sensitivity and Specificity Male Middle Aged Biomarkers Retrospective Studies Female Reproducibility of Results Tomography, Optical Coherence Macular Edema Fluorescein Angiography Subretinal Fluid Pseudophakia Diagnosis, Computer-Assisted Visual Acuity Predictive Value of Tests Humans Area Under Curve Diabetic Retinopathy Machine Learning
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Predicting Nondiagnostic Home Sleep Apnea Tests Using Machine Learning.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine Nov 15, 2019
STUDY OBJECTIVES: Home sleep apnea testing (HSAT) is an efficient and cost-effective method of diagnosing obstructive sleep apnea (OSA). However, nondiagnostic HSAT necessitates additional tests that erode these benefits, delaying diagnoses and incre...
Polysomnography Middle Aged Surveys and Questionnaires Sleep Apnea, Obstructive Calibration Decision Support Techniques Retrospective Studies Female Aged Humans Adult Machine Learning Self Care Sensitivity and Specificity Male
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[Computer instruments for the management of isolated pulmonary nodule. Detectability and prediction of malignancy].

Revue medicale suisse Nov 13, 2019
Lung cancer remains the most common cause of cancer deaths in the world, but its mortality can be significantly reduced by diagnosis and early detection. Computerized resources were developed to assist radiologists in their management of the large vo...
Humans Lung Neoplasms Artificial Intelligence Multiple Pulmonary Nodules Sensitivity and Specificity Diagnosis, Computer-Assisted
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How to Read Articles That Use Machine Learning: Users' Guides to the Medical Literature.

JAMA Nov 12, 2019
In recent years, many new clinical diagnostic tools have been developed using complicated machine learning methods. Irrespective of how a diagnostic tool is derived, it must be evaluated using a 3-step process of deriving, validating, and establishin...
Sensitivity and Specificity Humans Models, Theoretical Machine Learning Publications Algorithms
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