AIMC Topic: Sensitivity and Specificity

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Finger ECG based Two-phase Authentication Using 1D Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
This paper presents a study using 1D convolutional neural networks (CNNs) for ECG-based authentication. A simple CNN structure is used to both learn the features and do the classification automatically. Two types of CNNs are used in classification as...
Neural Networks, Computer Algorithms Sensitivity and Specificity Electrocardiography
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Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks.

JAMA ophthalmology Jul 1, 2018
IMPORTANCE: Retinopathy of prematurity (ROP) is a leading cause of childhood blindness worldwide. The decision to treat is primarily based on the presence of plus disease, defined as dilation and tortuosity of retinal vessels. However, clinical diagn...
Neural Networks, Computer Algorithms Female Infant, Newborn Humans Gestational Age Retinopathy of Prematurity Deep Learning Photography ROC Curve Retinal Vessels Image Interpretation, Computer-Assisted Infant, Premature Reproducibility of Results Sensitivity and Specificity Male Infant
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Deep-learning Classifier With an Ultrawide-field Scanning Laser Ophthalmoscope Detects Glaucoma Visual Field Severity.

Journal of glaucoma Jul 1, 2018
PURPOSE: To evaluate the accuracy of detecting glaucoma visual field defect severity using deep-learning (DL) classifier with an ultrawide-field scanning laser ophthalmoscope.
Cross-Sectional Studies Intraocular Pressure Male Middle Aged Humans Image Interpretation, Computer-Assisted Reproducibility of Results Glaucoma Aged Retrospective Studies Severity of Illness Index Visual Fields Adult Female Deep Learning Sensitivity and Specificity Visual Field Tests Microscopy, Confocal Ophthalmoscopes Vision Disorders
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[Comparison of machine learning method and logistic regression model in prediction of acute kidney injury in severely burned patients].

Zhonghua shao shang za zhi = Zhonghua shaoshang zazhi = Chinese journal of burns Jun 20, 2018
To build risk prediction models for acute kidney injury (AKI) in severely burned patients, and to compare the prediction performance of machine learning method and logistic regression model. The clinical data of 157 severely burned patients in Augu...
Organ Dysfunction Scores Explosions ROC Curve Logistic Models Humans Fluid Therapy Burns Machine Learning Acute Kidney Injury Hospitalization Sensitivity and Specificity Sepsis
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Texture Analysis and Machine Learning for Detecting Myocardial Infarction in Noncontrast Low-Dose Computed Tomography: Unveiling the Invisible.

Investigative radiology Jun 1, 2018
OBJECTIVES: The aim of this study was to test whether texture analysis and machine learning enable the detection of myocardial infarction (MI) on non-contrast-enhanced low radiation dose cardiac computed tomography (CCT) images.
Heart Myocardial Infarction Radiation Dosage Male Middle Aged Cluster Analysis Diagnosis, Differential Retrospective Studies Tomography, X-Ray Computed Female Reproducibility of Results Aged Aged, 80 and over Adult Sensitivity and Specificity Humans Machine Learning
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Using machine learning for sequence-level automated MRI protocol selection in neuroradiology.

Journal of the American Medical Informatics Association : JAMIA May 1, 2018
Incorrect imaging protocol selection can lead to important clinical findings being missed, contributing to both wasted health care resources and patient harm. We present a machine learning method for analyzing the unstructured text of clinical indica...
Datasets as Topic Neuroradiography Sensitivity and Specificity Humans Decision Support Systems, Clinical Machine Learning Support Vector Machine Magnetic Resonance Imaging
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Detection of high-grade small bowel obstruction on conventional radiography with convolutional neural networks.

Abdominal radiology (New York) May 1, 2018
The purpose of this pilot study is to determine whether a deep convolutional neural network can be trained with limited image data to detect high-grade small bowel obstruction patterns on supine abdominal radiographs. Grayscale images from 3663 clini...
Humans Neural Networks, Computer Female Aged Aged, 80 and over Young Adult Intestinal Obstruction Intestine, Small Pilot Projects Adult Adolescent Sensitivity and Specificity Radiography Male Image Interpretation, Computer-Assisted Middle Aged
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[Application of support vector machine in predicting in-hospital mortality risk of patients with acute kidney injury in ICU].

Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences Apr 18, 2018
OBJECTIVE: To construct an in-hospital mortality prediction model for patients with acute kidney injury (AKI) in intensive care unit (ICU) by using support vector machine (SVM), and compare it with the simplified acute physiology score II (SAPS-II) w...
Support Vector Machine Critical Care Intensive Care Units Humans Sensitivity and Specificity Prognosis Hospital Mortality Acute Kidney Injury ROC Curve
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Potential of artificial intelligence-assisted colonoscopy using an endocytoscope (with video).

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society Apr 1, 2018
Japan Humans Retrospective Studies Colonic Polyps Artificial Intelligence Colonoscopes Colonoscopy Video Recording Female Image Interpretation, Computer-Assisted Cohort Studies Sensitivity and Specificity Equipment Design Male Colonic Neoplasms
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Machine learning annotation of human branchpoints.

Bioinformatics (Oxford, England) Mar 15, 2018
MOTIVATION: The branchpoint element is required for the first lariat-forming reaction in splicing. However current catalogues of human branchpoints remain incomplete due to the difficulty in experimentally identifying these splicing elements. To addr...
Introns Sequence Analysis, DNA RNA Splicing Genetic Variation Humans Machine Learning Genome, Human Software Molecular Sequence Annotation Sensitivity and Specificity
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