AIMC Topic: Predictive Value of Tests

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Validation of a Deep Learning Algorithm for the Detection of Malignant Pulmonary Nodules in Chest Radiographs.

JAMA network open Sep 1, 2020
IMPORTANCE: The improvement of pulmonary nodule detection, which is a challenging task when using chest radiographs, may help to elevate the role of chest radiographs for the diagnosis of lung cancer.
Humans Artificial Intelligence Algorithms Female Reproducibility of Results Aged Solitary Pulmonary Nodule Early Detection of Cancer Predictive Value of Tests Radiologists Tumor Burden Radiography, Thoracic Radiographic Image Enhancement Sensitivity and Specificity Male Middle Aged Lung Deep Learning Lung Neoplasms
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Machine learning-based radiomics analysis in predicting the meningioma grade using multiparametric MRI.

European journal of radiology Aug 28, 2020
PURPOSE: To investigate the prediction performance of radiomic models based on multiparametric MRI in predicting the meningioma grade.
Predictive Value of Tests Humans Area Under Curve Machine Learning Neoplasm Grading Image Interpretation, Computer-Assisted Preoperative Care Retrospective Studies Meningeal Neoplasms Meningioma Female Multiparametric Magnetic Resonance Imaging Reproducibility of Results Male Middle Aged ROC Curve
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Biomarkers of the Response to Immune Checkpoint Inhibitors in Metastatic Urothelial Carcinoma.

Frontiers in immunology Aug 25, 2020
The mechanisms underlying the resistance to immune checkpoint inhibitors (ICIs) therapy in metastatic urothelial carcinoma (mUC) patients are not clear. It is of great significance to discern mUC patients who could benefit from ICI therapy in clinica...
Biomarkers, Tumor Humans Immune Checkpoint Inhibitors Predictive Value of Tests Male B7-H1 Antigen Machine Learning Carcinoma Risk Assessment Nomograms Decision Support Techniques Drug Resistance, Neoplasm Gene Expression Profiling Treatment Outcome Clinical Decision-Making Urothelium Transcriptome Antibodies, Monoclonal, Humanized Female Time Factors Urinary Bladder Neoplasms Risk Factors
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Predicting bovine tuberculosis status of dairy cows from mid-infrared spectral data of milk using deep learning.

Journal of dairy science Aug 20, 2020
Bovine tuberculosis (bTB) is a zoonotic disease in cattle that is transmissible to humans, distributed worldwide, and considered endemic throughout much of England and Wales. Mid-infrared (MIR) analysis of milk is used routinely to predict fat and pr...
Spectrophotometry, Infrared Scotland Tuberculosis, Bovine Animals Deep Learning England Cattle Predictive Value of Tests Neural Networks, Computer Lactation Phenotype Milk Female Sensitivity and Specificity
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Automated quantification of myocardial tissue characteristics from native T mapping using neural networks with uncertainty-based quality-control.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Aug 20, 2020
BACKGROUND: Tissue characterisation with cardiovascular magnetic resonance (CMR) parametric mapping has the potential to detect and quantify both focal and diffuse alterations in myocardial structure not assessable by late gadolinium enhancement. Nat...
Humans Cardiomyopathies Predictive Value of Tests Uncertainty Bayes Theorem Neural Networks, Computer Myocardium Reproducibility of Results Quality Control Ventricular Function, Left Image Interpretation, Computer-Assisted Stroke Volume Automation Case-Control Studies Magnetic Resonance Imaging
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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.
Humans Machine Learning Sex Factors Survival Analysis Internationality Belgium Clinical Laboratory Techniques Pneumonia, Viral China Cohort Studies Aged Hospital Mortality Predictive Value of Tests Adult Pandemics ROC Curve Male Triage Decision Support Systems, Clinical COVID-19 Middle Aged Area Under Curve Age Factors Retrospective Studies Risk Assessment Italy Female Severity of Illness Index Coronavirus Infections Reproducibility of Results COVID-19 Testing Hospitalization
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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...
Papillomavirus Infections Cervix Uteri Early Detection of Cancer Neoplasm Invasiveness Predictive Value of Tests Triage Biopsy Datasets as Topic Uterine Cervical Dysplasia Papillomaviridae Uterine Cervical Neoplasms Colposcopy Middle Aged Severity of Illness Index Deep Learning Image Processing, Computer-Assisted Vaginal Smears Humans Female Adult
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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...
Asymptomatic Diseases Diastole Unsupervised Machine Learning Predictive Value of Tests Peptide Fragments Heart Failure Ventricular Dysfunction, Left Humans Natriuretic Peptide, Brain Biomarkers Middle Aged Retrospective Studies Risk Assessment Female Disease Progression Diagnosis, Computer-Assisted Risk Factors Deep Learning Aged Cluster Analysis Aged, 80 and over Male Ventricular Function, Left Stroke Volume Echocardiography
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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...
Machine Learning Algorithms Female Reproducibility of Results Aged Aged, 80 and over Humans Predictive Value of Tests Registries Stroke Atrial Fibrillation Intracranial Embolism Male Middle Aged ROC Curve Image Processing, Computer-Assisted Electrocardiography Decision Trees
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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...
Aortic Aneurysm, Abdominal Radiographic Image Interpretation, Computer-Assisted Aorta, Abdominal Computed Tomography Angiography Aortography Humans Retrospective Studies Female Aged Aged, 80 and over Male Middle Aged Deep Learning Imaging, Three-Dimensional Predictive Value of Tests
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