AIMC Topic:
Predictive Value of Tests

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External validation of a convolutional neural network artificial intelligence tool to predict malignancy in pulmonary nodules.

Thorax Mar 5, 2020
BACKGROUND: Estimation of the risk of malignancy in pulmonary nodules detected by CT is central in clinical management. The use of artificial intelligence (AI) offers an opportunity to improve risk prediction. Here we compare the performance of an AI...
Humans Retrospective Studies Female Aged Adult Male Middle Aged Neural Networks, Computer Artificial Intelligence Algorithms Databases, Factual Prognosis Cell Transformation, Neoplastic Multiple Pulmonary Nodules Early Detection of Cancer Neoplasm Invasiveness Predictive Value of Tests Area Under Curve Neoplasm Staging Risk Assessment Incidence Cohort Studies ROC Curve Lung Neoplasms
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BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets.

Communications biology Mar 5, 2020
Understanding how cognitive functions emerge from brain structure depends on quantifying how discrete regions are integrated within the broader cortical landscape. Recent work established that macroscale brain organization and function can be describ...
Workflow Image Interpretation, Computer-Assisted Nerve Net Diffusion Tensor Imaging Neocortex Artificial Intelligence Reproducibility of Results Magnetic Resonance Imaging Brain Mapping Predictive Value of Tests Humans
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The impact of iterative reconstruction algorithms on machine learning-based coronary CT angiography-derived fractional flow reserve (CT-FFR) values.

The international journal of cardiovascular imaging Mar 4, 2020
To evaluate the impact of an iterative reconstruction (IR) algorithm (advanced modeled iterative reconstruction, ADMIRE) on machine learning-based coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) measurements compared...
Plaque, Atherosclerotic Vascular Calcification Computed Tomography Angiography Coronary Stenosis Fractional Flow Reserve, Myocardial Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Observer Variation Coronary Vessels Humans Machine Learning Retrospective Studies Reproducibility of Results Female Aged Male Middle Aged Severity of Illness Index Predictive Value of Tests
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Improved Accuracy in Optical Diagnosis of Colorectal Polyps Using Convolutional Neural Networks with Visual Explanations.

Gastroenterology Feb 29, 2020
BACKGROUND & AIMS: Narrow-band imaging (NBI) can be used to determine whether colorectal polyps are adenomatous or hyperplastic. We investigated whether an artificial intelligence (AI) system can increase the accuracy of characterizations of polyps b...
Observer Variation Hyperplasia Humans Deep Learning Visual Perception Narrow Band Imaging Reproducibility of Results Seoul Clinical Competence Colorectal Neoplasms Adenomatous Polyps Predictive Value of Tests Colonoscopy Workflow Diagnosis, Computer-Assisted Colonic Polyps Image Interpretation, Computer-Assisted
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Noninvasive Diagnosis of Nonalcoholic Fatty Liver Disease and Quantification of Liver Fat with Radiofrequency Ultrasound Data Using One-dimensional Convolutional Neural Networks.

Radiology Feb 25, 2020
Background Radiofrequency ultrasound data from the liver contain rich information about liver microstructure and composition. Deep learning might exploit such information to assess nonalcoholic fatty liver disease (NAFLD). Purpose To develop and eval...
Predictive Value of Tests Non-alcoholic Fatty Liver Disease Random Allocation Radio Waves Male Middle Aged Ultrasonography Image Processing, Computer-Assisted Humans Magnetic Resonance Imaging Neural Networks, Computer Prospective Studies Female Sensitivity and Specificity
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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...
Heart Failure Patient Readmission Cloud Computing Telemetry Time Factors Humans Smartphone Machine Learning United States Predictive Value of Tests Equipment Design Aged, 80 and over Male Middle Aged Risk Assessment Diagnosis, Computer-Assisted Wearable Electronic Devices Prognosis Female Reproducibility of Results Risk Factors Aged
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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...
Prospective Studies Female Aged Male Middle Aged Disease Progression Diagnosis, Computer-Assisted Time Factors Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Humans Machine Learning Registries Coronary Artery Disease Multidetector Computed Tomography 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...
Humans Decision Support Systems, Clinical Treatment Outcome Predictive Value of Tests Aortic Aneurysm, Abdominal Patient Selection Image Interpretation, Computer-Assisted Artificial Intelligence Decision Support Techniques Clinical Decision-Making Risk Factors Risk Assessment Diagnosis, 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 ...
Lung Neoplasms Carcinoma, Non-Small-Cell Lung Predictive Value of Tests Positron Emission Tomography Computed Tomography Mutation Radiopharmaceuticals Image Interpretation, Computer-Assisted Fluorodeoxyglucose F18 ErbB Receptors Imaging Genomics Female Reproducibility of Results Aged Sensitivity and Specificity 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...
Asymptomatic Diseases Aged, 80 and over Pericardium Male Middle Aged Risk Assessment Deep Learning Adipose Tissue Predictive Value of Tests Coronary Angiography Humans Coronary Artery Disease Prognosis Coronary Vessels Tomography, X-Ray Computed Vascular Calcification Female Risk Factors Aged
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