AIMC Topic: Predictive Value of Tests

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Continuous Wearable Monitoring Analytics Predict Heart Failure Hospitalization: The LINK-HF Multicenter Study.

Circulation. Heart failure Feb 25, 2020
BACKGROUND: Implantable cardiac sensors have shown promise in reducing rehospitalization for heart failure (HF), but the efficacy of noninvasive approaches has not been determined. The objective of this study was to determine the accuracy of noninvas...
Male Middle Aged Risk Assessment Diagnosis, Computer-Assisted Wearable Electronic Devices Time Factors Smartphone United States Predictive Value of Tests Equipment Design Heart Failure Female Reproducibility of Results Risk Factors Aged Aged, 80 and over Humans Machine Learning Prognosis Patient Readmission Cloud Computing Telemetry
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Machine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis: From the PARADIGM Registry.

Journal of the American Heart Association Feb 22, 2020
Background Rapid coronary plaque progression (RPP) is associated with incident cardiovascular events. To date, no method exists for the identification of individuals at risk of RPP at a single point in time. This study integrated coronary computed to...
Disease Progression Diagnosis, Computer-Assisted Time Factors Predictive Value of Tests Coronary Angiography Prospective Studies Humans Radiographic Image Interpretation, Computer-Assisted Female Machine Learning Registries Aged Coronary Artery Disease Male Multidetector Computed Tomography Middle Aged Plaque, Atherosclerotic Computed Tomography Angiography
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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...
Diagnosis, Computer-Assisted Decision Support Systems, Clinical Treatment Outcome Predictive Value of Tests Aortic Aneurysm, Abdominal Artificial Intelligence Decision Support Techniques Clinical Decision-Making Risk Factors Patient Selection Humans Risk Assessment Image Interpretation, Computer-Assisted
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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 ...
Male Lung Lung Neoplasms Carcinoma, Non-Small-Cell Lung Predictive Value of Tests Retrospective Studies Female Reproducibility of Results Aged Sensitivity and Specificity ErbB Receptors Imaging Genomics Positron Emission Tomography Computed Tomography Mutation Radiopharmaceuticals Image Interpretation, Computer-Assisted Fluorodeoxyglucose F18 Humans Machine Learning
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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...
Deep Learning Adipose Tissue Predictive Value of Tests Coronary Angiography Coronary Artery Disease Coronary Vessels Vascular Calcification Asymptomatic Diseases Pericardium Aged Aged, 80 and over Male Middle Aged Risk Assessment Humans Prognosis Tomography, X-Ray Computed 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...
Linear Models Intra-Abdominal Fat Magnetic Resonance Imaging Humans Female Neural Networks, Computer Predictive Value of Tests Reproducibility of Results Radiographic Image Interpretation, Computer-Assisted Aged Anthropometry Male Adiposity Middle Aged United Kingdom
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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 Prospective Studies Female Diagnosis, Computer-Assisted Deep Learning Adolescent Treatment Outcome Wound Healing Colitis, Ulcerative Predictive Value of Tests Biopsy Remission Induction Image Interpretation, Computer-Assisted Male Middle Aged Colon Colonoscopy Severity of Illness Index Reproducibility of Results Aged Aged, 80 and over Young Adult Adult
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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...
Sensitivity and Specificity Diagnosis, Computer-Assisted Support Vector Machine Predictive Value of Tests Obesity, Abdominal Adiposity Humans Algorithms Risk Factors
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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...
Carbapenems DNA, Bacterial Humans Cross Infection Klebsiella Infections Algorithms Carbapenem-Resistant Enterobacteriaceae Predictive Value of Tests Anti-Bacterial Agents Random Amplified Polymorphic DNA Technique Supervised Machine Learning Microbial Sensitivity Tests Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Klebsiella pneumoniae
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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...
Aminolevulinic Acid Margins of Excision Protoporphyrins Humans Cell Line, Tumor Machine Learning Glioma Computer Simulation Cluster Analysis Prognosis Predictive Value of Tests Biomarkers, Tumor Spectrometry, Fluorescence Brain Neoplasms Pilot Projects
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