AIMC Topic: Predictive Value of Tests

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Artificial intelligence in abdominal aortic aneurysm.

Journal of vascular surgery Feb 21, 2020
OBJECTIVE: Abdominal aortic aneurysm (AAA) is a life-threatening disease, and the only curative treatment relies on open or endovascular repair. The decision to treat relies on the evaluation of the risk of AAA growth and rupture, which can be diffic...
Treatment Outcome Predictive Value of Tests Aortic Aneurysm, Abdominal Patient Selection Image Interpretation, Computer-Assisted Risk Factors Risk Assessment Diagnosis, Computer-Assisted Decision Support Systems, Clinical Artificial Intelligence Decision Support Techniques Clinical Decision-Making Humans
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Radiogenomic Models Using Machine Learning Techniques to Predict EGFR Mutations in Non-Small Cell Lung Cancer.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes Feb 17, 2020
BACKGROUND: The purpose of this study was to build radiogenomics models from texture signatures derived from computed tomography (CT) and F-FDG PET-CT (FDG PET-CT) images of non-small cell lung cancer (NSCLC) with and without epidermal growth factor ...
Fluorodeoxyglucose F18 ErbB Receptors Imaging Genomics Positron Emission Tomography Computed Tomography Mutation Radiopharmaceuticals Image Interpretation, Computer-Assisted Female Reproducibility of Results Aged Sensitivity and Specificity Lung Neoplasms Carcinoma, Non-Small-Cell Lung Predictive Value of Tests Male Lung Humans Machine Learning Retrospective Studies
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Deep Learning-Based Quantification of Epicardial Adipose Tissue Volume and Attenuation Predicts Major Adverse Cardiovascular Events in Asymptomatic Subjects.

Circulation. Cardiovascular imaging Feb 17, 2020
BACKGROUND: Epicardial adipose tissue (EAT) volume (cm) and attenuation (Hounsfield units) may predict major adverse cardiovascular events (MACE). We aimed to evaluate the prognostic value of fully automated deep learning-based EAT volume and attenua...
Pericardium Aged Coronary Artery Disease Aged, 80 and over Coronary Vessels Male Humans Vascular Calcification Middle Aged Adipose Tissue Prognosis Asymptomatic Diseases Risk Assessment Predictive Value of Tests Tomography, X-Ray Computed Deep Learning Coronary Angiography Female Risk Factors
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Novel artificial neural network and linear regression based equation for estimating visceral adipose tissue volume.

Clinical nutrition (Edinburgh, Scotland) Feb 14, 2020
BACKGROUND: There is a growing interest in fast and reliable assessment of abdominal visceral adipose tissue (VAT) volume for risk stratification of metabolic disorders. However, imaging based measurement of VAT is costly and limited by scanner avail...
Female Reproducibility of Results Aged Male Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Anthropometry Middle Aged Magnetic Resonance Imaging Humans Neural Networks, Computer Adiposity United Kingdom Linear Models Intra-Abdominal Fat
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Development and Validation of a Deep Neural Network for Accurate Evaluation of Endoscopic Images From Patients With Ulcerative Colitis.

Gastroenterology Feb 12, 2020
BACKGROUND & AIMS: There are intra- and interobserver variations in endoscopic assessment of ulcerative colitis (UC) and biopsies are often collected for histologic evaluation. We sought to develop a deep neural network system for consistent, objecti...
Humans Databases, Factual Aged, 80 and over Young Adult Adult Male Middle Aged Prospective Studies Female Reproducibility of Results Aged Colitis, Ulcerative Deep Learning Predictive Value of Tests Colon Adolescent Biopsy Colonoscopy Image Interpretation, Computer-Assisted Treatment Outcome Remission Induction Severity of Illness Index Wound Healing Diagnosis, Computer-Assisted
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The Prediction of Human Abdominal Adiposity Based on the Combination of a Particle Swarm Algorithm and Support Vector Machine.

International journal of environmental research and public health Feb 10, 2020
: Abdominal adiposity is an important risk factor of chronic cardiovascular diseases, thus the prediction of abdominal adiposity and obesity can reduce the risks of contracting such diseases. However, the current prediction models display low accurac...
Diagnosis, Computer-Assisted Support Vector Machine Predictive Value of Tests Obesity, Abdominal Adiposity Humans Algorithms Risk Factors Sensitivity and Specificity
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Detection of carbapenem-resistant Klebsiella pneumoniae on the basis of matrix-assisted laser desorption ionization time-of-flight mass spectrometry by using supervised machine learning approach.

PloS one Feb 6, 2020
BACKGROUND: Carbapenem-resistant Klebsiella pneumoniae (CRKP) is emerging as a significant pathogen causing healthcare-associated infections. Matrix-assisted laser desorption/ionisation mass spectrometry time-of-flight mass spectrometry (MALDI-TOF MS...
Cross Infection Humans Anti-Bacterial Agents Supervised Machine Learning Carbapenem-Resistant Enterobacteriaceae Microbial Sensitivity Tests Algorithms Klebsiella Infections Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Klebsiella pneumoniae Random Amplified Polymorphic DNA Technique Predictive Value of Tests Carbapenems DNA, Bacterial
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Machine learning-based prediction of glioma margin from 5-ALA induced PpIX fluorescence spectroscopy.

Scientific reports Jan 29, 2020
Gliomas are infiltrative brain tumors with a margin difficult to identify. 5-ALA induced PpIX fluorescence measurements are a clinical standard, but expert-based classification models still lack sensitivity and specificity. Here a fully automatic clu...
Machine Learning Protoporphyrins Computer Simulation Prognosis Biomarkers, Tumor Cluster Analysis Predictive Value of Tests Brain Neoplasms Spectrometry, Fluorescence Humans Pilot Projects Aminolevulinic Acid Cell Line, Tumor Margins of Excision Glioma
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Are neural networks the ultimate risk prediction models in patients at high risk of acute myocardial infarction?

European journal of preventive cardiology Jan 28, 2020
Predictive Value of Tests Myocardial Infarction Humans Neural Networks, Computer Risk Assessment
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A machine-learning approach to predicting hypotensive events in ICU settings.

Computers in biology and medicine Jan 24, 2020
BACKGROUND: Predicting hypotension well in advance provides physicians with enough time to respond with proper therapeutic measures. However, the real-time prediction of hypotension with high positive predictive value (PPV) is a challenge. This is du...
Predictive Value of Tests Humans Hypotension Machine Learning Algorithms Intensive Care Units
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