AIMC Topic: Sensitivity and Specificity

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A RR interval based automated apnea detection approach using residual network.

Computer methods and programs in biomedicine May 8, 2019
BACKGROUND AND OBJECTIVE: Apnea is one of the most common conditions that causes sleep-disorder breathing. With growing number of patients worldwide, more and more patients suffer from complications of apnea. But most of them stay untreated due to th...
Humans Neural Networks, Computer Algorithms Female Reproducibility of Results Adult Sensitivity and Specificity Signal Processing, Computer-Assisted Sleep Apnea Syndromes Respiration Polysomnography Male Middle Aged Electrocardiography Support Vector Machine
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Prediction of hematoma expansion in spontaneous intracerebral hemorrhage using support vector machine.

EBioMedicine May 3, 2019
BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) is a devastating disease with high mortality rate. This study aimed to predict hematoma expansion in spontaneous ICH from routinely available variables by using support vector machine (SVM) metho...
Male Middle Aged ROC Curve Image Processing, Computer-Assisted Support Vector Machine Aged, 80 and over Young Adult Adult Sensitivity and Specificity Cerebral Hemorrhage Models, Biological Hematoma Odds Ratio Glasgow Coma Scale Humans Biomarkers Prognosis Retrospective Studies Tomography, X-Ray Computed Female Aged
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Deep learning enables automatic detection and segmentation of brain metastases on multisequence MRI.

Journal of magnetic resonance imaging : JMRI May 2, 2019
BACKGROUND: Detecting and segmenting brain metastases is a tedious and time-consuming task for many radiologists, particularly with the growing use of multisequence 3D imaging.
Humans Brain Retrospective Studies Female Aged Middle Aged Adult Deep Learning Sensitivity and Specificity Magnetic Resonance Imaging Brain Neoplasms Image Interpretation, Computer-Assisted Male
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Artificial intelligence using deep learning to screen for referable and vision-threatening diabetic retinopathy in Africa: a clinical validation study.

The Lancet. Digital health May 2, 2019
BACKGROUND: Radical measures are required to identify and reduce blindness due to diabetes to achieve the Sustainable Development Goals by 2030. Therefore, we evaluated the accuracy of an artificial intelligence (AI) model using deep learning in a po...
Humans Diabetic Retinopathy Neural Networks, Computer Artificial Intelligence Prospective Studies Mass Screening Area Under Curve Retina Photography Zambia Female Adult Sensitivity and Specificity Male Deep Learning
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Importance of coding co-morbidities for APR-DRG assignment: Focus on cardiovascular and respiratory diseases.

Health information management : journal of the Health Information Management Association of Australia May 1, 2019
BACKGROUND: The All Patient-Refined Diagnosis-Related Groups (APR-DRGs) system has adjusted the basic DRG structure by incorporating four severity of illness (SOI) levels, which are used for determining hospital payment. A comprehensive report of all...
Respiratory Tract Diseases Portugal Diagnosis-Related Groups Hospital Charges Comorbidity Humans Female Severity of Illness Index Sensitivity and Specificity Support Vector Machine Male Quality Control Cardiovascular Diseases Data Accuracy
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A deep learning radiomics model for preoperative grading in meningioma.

European journal of radiology May 1, 2019
OBJECTIVES: To noninvasively differentiate meningioma grades by deep learning radiomics (DLR) model based on routine post-contrast MRI.
Meningeal Neoplasms Meninges Algorithms Magnetic Resonance Imaging Prognosis Area Under Curve Retrospective Studies Neoplasm Grading Female Preoperative Care Reproducibility of Results Middle Aged Meningioma Deep Learning Aged Humans Adolescent Young Adult Cohort Studies Adult Sensitivity and Specificity Male
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Effect of Tube Voltage on Diagnostic Performance of Fractional Flow Reserve Derived From Coronary CT Angiography With Machine Learning: Results From the MACHINE Registry.

AJR. American journal of roentgenology Apr 30, 2019
Coronary CT angiography (CCTA)-based methods allow noninvasive estimation of fractional flow reserve (cFFR), recently through use of a machine learning (ML) algorithm (cFFR). However, attenuation values vary according to the tube voltage used, and i...
Machine Learning Registries Retrospective Studies Coronary Disease Female Computed Tomography Angiography Sensitivity and Specificity Aged Humans Fractional Flow Reserve, Myocardial Male Middle Aged Predictive Value of Tests Coronary Angiography
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Deep Learning for Diagnosis of Chronic Myocardial Infarction on Nonenhanced Cardiac Cine MRI.

Radiology Apr 30, 2019
Background Renal impairment is common in patients with coronary artery disease and, if severe, late gadolinium enhancement (LGE) imaging for myocardial infarction (MI) evaluation cannot be performed. Purpose To develop a fully automatic framework for...
Humans Databases, Factual Retrospective Studies Female Aged Deep Learning Adult Chronic Disease Sensitivity and Specificity Myocardial Infarction Male Image Interpretation, Computer-Assisted Middle Aged Magnetic Resonance Imaging, Cine
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A Novel Method for Classifying Liver and Brain Tumors Using Convolutional Neural Networks, Discrete Wavelet Transform and Long Short-Term Memory Networks.

Sensors (Basel, Switzerland) Apr 28, 2019
Rapid classification of tumors that are detected in the medical images is of great importance in the early diagnosis of the disease. In this paper, a new liver and brain tumor classification method is proposed by using the power of convolutional neur...
Wavelet Analysis Meningioma Brain Neoplasms Liver Neoplasms Glioma Support Vector Machine Pituitary Neoplasms Humans Neural Networks, Computer Tomography, X-Ray Computed Sensitivity and Specificity
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Assessment of Electrocardiogram Rhythms by GoogLeNet Deep Neural Network Architecture.

Journal of healthcare engineering Apr 28, 2019
The aim of this study is to design GoogLeNet deep neural network architecture by expanding the kernel size of the inception layer and combining the convolution layers to classify the electrocardiogram (ECG) beats into a normal sinus rhythm, premature...
Electrocardiography Humans Databases, Factual Signal Processing, Computer-Assisted Sensitivity and Specificity Internet Deep Learning Arrhythmias, Cardiac
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