AI Medical Compendium Topic:
Predictive Value of Tests

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Development of a clinical decision support system for severity risk prediction and triage of COVID-19 patients at hospital admission: an international multicentre study.

The European respiratory journal Aug 20, 2020
BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has globally strained medical resources and caused significant mortality.
China Cohort Studies Hospital Mortality ROC Curve Decision Support Systems, Clinical Age Factors Aged Adult Male Middle Aged Risk Assessment Severity of Illness Index Sex Factors Survival Analysis Internationality Belgium Clinical Laboratory Techniques Pneumonia, Viral Humans Machine Learning Pandemics Predictive Value of Tests COVID-19 Triage Retrospective Studies Area Under Curve Female Italy Reproducibility of Results Coronavirus Infections Hospitalization COVID-19 Testing
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Artificial intelligence-assisted cytology for detection of cervical intraepithelial neoplasia or invasive cancer: A multicenter, clinical-based, observational study.

Gynecologic oncology Aug 16, 2020
OBJECTIVE: Artificial intelligence (AI) could automatedly detect abnormalities in digital cytological images, however, the effect in cervical cancer screening is inconclusive. We aim to evaluate the performance of AI-assisted cytology for the detecti...
Triage Biopsy Datasets as Topic Uterine Cervical Dysplasia Papillomaviridae Colposcopy Vaginal Smears Papillomavirus Infections Cervix Uteri Adult Early Detection of Cancer Neoplasm Invasiveness Humans Uterine Cervical Neoplasms Predictive Value of Tests Female Middle Aged Severity of Illness Index Deep Learning Image Processing, Computer-Assisted
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Identifying Phenogroups in patients with subclinical diastolic dysfunction using unsupervised statistical learning.

BMC cardiovascular disorders Aug 14, 2020
BACKGROUND: Subclinical diastolic dysfunction is a precursor for developing heart failure with preserved ejection fraction (HFpEF); yet not all patients progress to HFpEF. Our objective was to evaluate clinical and echocardiographic variables to iden...
Peptide Fragments Male Heart Failure Ventricular Function, Left Ventricular Dysfunction, Left Stroke Volume Natriuretic Peptide, Brain Echocardiography Asymptomatic Diseases Middle Aged Biomarkers Diastole Risk Assessment Disease Progression Retrospective Studies Humans Diagnosis, Computer-Assisted Female Deep Learning Risk Factors Cluster Analysis Aged Unsupervised Machine Learning Aged, 80 and over Predictive Value of Tests
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Machine Learning Prediction of Stroke Mechanism in Embolic Strokes of Undetermined Source.

Stroke Aug 12, 2020
BACKGROUND AND PURPOSE: One-fifth of ischemic strokes are embolic strokes of undetermined source (ESUS). Their theoretical causes can be classified as cardioembolic versus noncardioembolic. This distinction has important implications, but the categor...
ROC Curve Image Processing, Computer-Assisted Electrocardiography Decision Trees Predictive Value of Tests Registries Female Reproducibility of Results Aged Aged, 80 and over Male Middle Aged Stroke Atrial Fibrillation Intracranial Embolism Humans Machine Learning Algorithms
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3D Automatic Segmentation of Aortic Computed Tomography Angiography Combining Multi-View 2D Convolutional Neural Networks.

Cardiovascular engineering and technology Aug 11, 2020
PURPOSE: The quantitative analysis of contrast-enhanced Computed Tomography Angiography (CTA) is essential to assess aortic anatomy, identify pathologies, and perform preoperative planning in vascular surgery. To overcome the limitations given by man...
Middle Aged Deep Learning Imaging, Three-Dimensional Predictive Value of Tests Aortic Aneurysm, Abdominal Radiographic Image Interpretation, Computer-Assisted Humans Aorta, Abdominal Retrospective Studies Computed Tomography Angiography Female Aortography Aged Aged, 80 and over Male
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Effect of vessel wall segmentation on volumetric and radiomic parameters of coronary plaques with adverse characteristics.

Journal of cardiovascular computed tomography Aug 10, 2020
BACKGROUND: Quantitative coronary plaque parameters are increasingly being utilized as surrogate endpoints of pharmaceutical trials. However, little is known whether differences in segmentation significantly alter parameter values.
Clinical Competence Predictive Value of Tests Humans Female Machine Learning Coronary Angiography Coronary Vessels Radiographic Image Interpretation, Computer-Assisted Retrospective Studies Reproducibility of Results Plaque, Atherosclerotic Coronary Artery Disease Aged Vascular Calcification Observer Variation Male Computed Tomography Angiography Middle Aged Severity of Illness Index
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A machine learning approach identified a diagnostic model for pancreatic cancer through using circulating microRNA signatures.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.] Aug 9, 2020
Late diagnosis of pancreatic cancer (PC) due to the limited effectiveness of modern testing approaches, causes many patients to miss the chance of surgery and consequently leads to a high mortality rate. Pivotal improvements in circulating microRNA e...
Humans Neural Networks, Computer Machine Learning Algorithms Reproducibility of Results Sensitivity and Specificity Computational Biology Gene Expression Regulation, Neoplastic Early Detection of Cancer MicroRNAs Pancreatic Neoplasms Predictive Value of Tests Principal Component Analysis Survival Analysis Microarray Analysis Kaplan-Meier Estimate Circulating MicroRNA
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Reliability and accuracy of EEG interpretation for estimating age in preterm infants.

Annals of clinical and translational neurology Aug 7, 2020
OBJECTIVES: To determine the accuracy of, and agreement among, EEG and aEEG readers' estimation of maturity and a novel computational measure of functional brain age (FBA) in preterm infants.
Infant, Newborn Reproducibility of Results Diagnosis, Computer-Assisted Predictive Value of Tests Electroencephalography Brain Diseases Humans Machine Learning Brain Infant, Premature Gestational Age Neonatology
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Artificial intelligence assistance significantly improves Gleason grading of prostate biopsies by pathologists.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc Aug 5, 2020
The Gleason score is the most important prognostic marker for prostate cancer patients, but it suffers from significant observer variability. Artificial intelligence (AI) systems based on deep learning can achieve pathologist-level performance at Gle...
Pathologists Microscopy Image Interpretation, Computer-Assisted Observer Variation Diagnosis, Computer-Assisted Deep Learning Predictive Value of Tests Prostatic Neoplasms Neoplasm Grading Biopsy Humans Reproducibility of Results Male
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Artificial Intelligence-Enabled ECG Algorithm to Identify Patients With Left Ventricular Systolic Dysfunction Presenting to the Emergency Department With Dyspnea.

Circulation. Arrhythmia and electrophysiology Aug 4, 2020
BACKGROUND: Identification of systolic heart failure among patients presenting to the emergency department (ED) with acute dyspnea is challenging. The reasons for dyspnea are often multifactorial. A focused physical evaluation and diagnostic testing ...
Electrocardiography Predictive Value of Tests Emergency Medical Services Heart Failure, Systolic Humans Aged Signal Processing, Computer-Assisted Artificial Intelligence Systole Male Dyspnea Retrospective Studies Cardiology Service, Hospital Ventricular Dysfunction, Left Ventricular Function, Left Female Stroke Volume Reproducibility of Results Middle Aged Diagnosis, Computer-Assisted
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