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Dimensional Measurement Accuracy

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Semiautomatic Three-Dimensional Threshold-Based Cardiac Computed Tomography Ventricular Volumetry in Repaired Tetralogy of Fallot: Comparison with Cardiac Magnetic Resonance Imaging.

Korean journal of radiology 30627026
OBJECTIVE: To assess the accuracy and potential bias of computed tomography (CT) ventricular volumetry using semiautomatic three-dimensional (3D) threshold-based segmentation in repaired tetralogy of Fallot, and to compare them to those of two-dimens...
Adolescent Adult Cardiac Surgical Procedures Child Cone-Beam Computed Tomography Dimensional Measurement Accuracy Female Heart Ventricles Humans Magnetic Resonance Imaging Male Retrospective Studies Stroke Volume Tetralogy of Fallot Young Adult
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Predicting protein conformational changes for unbound and homology docking: learning from intrinsic and induced flexibility.

Proteins 27862345
Predicting protein conformational changes from unbound structures or even homology models to bound structures remains a critical challenge for protein docking. Here we present a study directly addressing the challenge by reducing the dimensionality a...
Benchmarking Binding Sites Computational Biology Dimensional Measurement Accuracy Machine Learning Models, Statistical Molecular Docking Simulation Protein Binding Protein Conformation Protein Multimerization Proteins Research Design Software Structural Homology, Protein Thermodynamics
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Diagnostic assessment of a deep learning system for detecting atrial fibrillation in pulse waveforms.

Heart (British Cardiac Society) 29853485
OBJECTIVE: To evaluate the diagnostic performance of a deep learning system for automated detection of atrial fibrillation (AF) in photoplethysmographic (PPG) pulse waveforms.
Aged Atrial Fibrillation Comparative Effectiveness Research Deep Learning Dimensional Measurement Accuracy Electrocardiography Female Humans Male Middle Aged Monitoring, Ambulatory Photoplethysmography Sensitivity and Specificity Smartphone Telemedicine Ventricular Premature Complexes
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Natural Language Processing to Identify Pulmonary Nodules and Extract Nodule Characteristics From Radiology Reports.

Chest 34089738
BACKGROUND: There is an urgent need for population-based studies on managing patients with pulmonary nodules.
Algorithms Calcinosis Dimensional Measurement Accuracy Documentation Humans Lung Lung Neoplasms Multiple Pulmonary Nodules Natural Language Processing Quality Improvement Radiography, Thoracic Radiology Sensitivity and Specificity Solitary Pulmonary Nodule Tomography, X-Ray Computed Tumor Burden
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