AIMC Topic: Predictive Value of Tests

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Deep learning analysis in coronary computed tomographic angiography imaging for the assessment of patients with coronary artery stenosis.

Computer methods and programs in biomedicine Jul 9, 2020
BACKGROUND AND OBJECTIVE: Recently, deep convolutional neural network has significantly improved image classification and image segmentation. If coronary artery disease (CAD) can be diagnosed through machine learning and deep learning, it will signif...
Deep Learning Humans Coronary Stenosis Predictive Value of Tests Artificial Intelligence Coronary Angiography Retrospective Studies Coronary Artery Disease Tomography, X-Ray Computed Coronary Vessels
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Diagnostic performance of fetal intelligent navigation echocardiography (FINE) in fetuses with double-outlet right ventricle (DORV).

The international journal of cardiovascular imaging Jul 8, 2020
The main objective of this study was to investigate the diagnostic performance of FINE in generating and displaying 3 specific abnormal fetal echocardiography views such as left ventricular outflow tract (LVOT) view, right ventricular outflow tract (...
Young Adult Adult Ultrasonography, Prenatal Spatio-Temporal Analysis Diagnosis, Computer-Assisted Humans Predictive Value of Tests Artificial Intelligence Anatomic Landmarks Pregnancy Image Interpretation, Computer-Assisted Female Gestational Age Double Outlet Right Ventricle Reproducibility of Results Fetal Heart Echocardiography, Four-Dimensional
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Artificial intelligence to predict clinical disability in patients with multiple sclerosis using FLAIR MRI.

Diagnostic and interventional imaging Jul 7, 2020
PURPOSE: The purpose of this study was to create an algorithm that combines multiple machine-learning techniques to predict the expanded disability status scale (EDSS) score of patients with multiple sclerosis at two years solely based on age, sex an...
Humans Neural Networks, Computer Artificial Intelligence Brain Magnetic Resonance Imaging Predictive Value of Tests Multiple Sclerosis
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Radiomics can predict tumour response in patients treated with Nivolumab for a metastatic renal cell carcinoma: an artificial intelligence concept.

World journal of urology Jul 6, 2020
Treatment Outcome Predictive Value of Tests Nivolumab Kidney Neoplasms Carcinoma, Renal Cell Male Middle Aged Cohort Studies Immune Checkpoint Inhibitors Image Processing, Computer-Assisted Algorithms Humans Tomography, X-Ray Computed Female Artificial Intelligence Aged
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Machine Learning to Classify Intracardiac Electrical Patterns During Atrial Fibrillation: Machine Learning of Atrial Fibrillation.

Circulation. Arrhythmia and electrophysiology Jul 6, 2020
BACKGROUND: Advances in ablation for atrial fibrillation (AF) continue to be hindered by ambiguities in mapping, even between experts. We hypothesized that convolutional neural networks (CNN) may enable objective analysis of intracardiac activation i...
Humans Neural Networks, Computer Female Reproducibility of Results Registries Time Factors Support Vector Machine Atrial Fibrillation Aged Action Potentials Electrophysiologic Techniques, Cardiac Heart Rate Male Predictive Value of Tests Atrial Function, Right Middle Aged Pattern Recognition, Automated Signal Processing, Computer-Assisted Atrial Function, Left Diagnosis, Computer-Assisted
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Artificial Intelligence and Machine Learning in Arrhythmias and Cardiac Electrophysiology.

Circulation. Arrhythmia and electrophysiology Jul 6, 2020
Artificial intelligence (AI) and machine learning (ML) in medicine are currently areas of intense exploration, showing potential to automate human tasks and even perform tasks beyond human capabilities. Literacy and understanding of AI/ML methods are...
Predictive Value of Tests Signal Processing, Computer-Assisted Heart Conduction System Arrhythmias, Cardiac Heart Rate Diagnosis, Computer-Assisted Deep Learning Electrocardiography Action Potentials Electrophysiologic Techniques, Cardiac Humans Artificial Intelligence Machine Learning Prognosis Reproducibility of Results
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Ischemia and outcome prediction by cardiac CT based machine learning.

The international journal of cardiovascular imaging Jul 4, 2020
Cardiac CT using non-enhanced coronary artery calcium scoring (CACS) and coronary CT angiography (cCTA) has been proven to provide excellent evaluation of coronary artery disease (CAD) combining anatomical and morphological assessment of CAD for card...
Risk Assessment Severity of Illness Index Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Humans Machine Learning Prognosis Reproducibility of Results Vascular Calcification Computed Tomography Angiography Coronary Artery Disease Heart Disease Risk Factors Coronary Vessels Plaque, Atherosclerotic
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Prediction of hERG potassium channel blockage using ensemble learning methods and molecular fingerprints.

Toxicology letters Jul 3, 2020
The human ether-a-go-go-related gene (hERG) encodes a tetrameric potassium channel called Kv11.1. This channel can be blocked by certain drugs, which leads to long QT syndrome, causing cardiotoxicity. This is a significant problem during drug develop...
Peptide Mapping Cardiotoxicity Potassium Channel Blockers ERG1 Potassium Channel CHO Cells Cricetulus Area Under Curve Models, Molecular Cricetinae Databases, Factual Animals Support Vector Machine Predictive Value of Tests Humans Machine Learning Algorithms
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Machine learning-based prediction of acute severity in infants hospitalized for bronchiolitis: a multicenter prospective study.

Scientific reports Jul 3, 2020
We aimed to develop machine learning models to accurately predict bronchiolitis severity, and to compare their predictive performance with a conventional scoring (reference) model. In a 17-center prospective study of infants (aged < 1 year) hospitali...
Predictive Value of Tests Intensive Care Units Infant Humans Positive-Pressure Respiration Female Severity of Illness Index Bronchiolitis Hospitalization Machine Learning Cohort Studies Male Prospective Studies Regression Analysis Decision Trees
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From CT to artificial intelligence for complex assessment of plaque-associated risk.

The international journal of cardiovascular imaging Jul 2, 2020
The recent technological developments in the field of cardiac imaging have established coronary computed tomography angiography (CCTA) as a first-line diagnostic tool in patients with suspected coronary artery disease (CAD). CCTA offers robust inform...
Machine Learning Prognosis Reproducibility of Results Risk Assessment Severity of Illness Index Humans Coronary Vessels Rupture, Spontaneous Plaque, Atherosclerotic Computed Tomography Angiography Predictive Value of Tests Coronary Stenosis Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Heart Disease Risk Factors
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