AIMC Topic: Registries

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Machine learning application for incident prostate adenocarcinomas automatic registration in a French regional cancer registry.

International journal of medical informatics Apr 9, 2020
UNLABELLED: Cancer registries are collections of curated data about malignant tumor diseases. The amount of data processed by cancer registries increases every year, making manual registration more and more tedious.
Registries Data Mining France International Classification of Diseases Algorithms Male Incidence Adenocarcinoma Prostatic Neoplasms Humans Machine Learning
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Machine-Learning prediction of comorbid substance use disorders in ADHD youth using Swedish registry data.

Journal of child psychology and psychiatry, and allied disciplines Apr 1, 2020
BACKGROUND: Children with attention-deficit/hyperactivity disorder (ADHD) have a high risk for substance use disorders (SUDs). Early identification of at-risk youth would help allocate scarce resources for prevention programs.
Humans Adolescent Child, Preschool Child Machine Learning Substance-Related Disorders Sweden Registries Risk Factors Attention Deficit Disorder with Hyperactivity Cross-Sectional Studies Comorbidity
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Interpatient Similarities in Cardiac Function: A Platform for Personalized Cardiovascular Medicine.

JACC. Cardiovascular imaging Mar 18, 2020
OBJECTIVES: The authors applied unsupervised machine-learning techniques for integrating echocardiographic features of left ventricular (LV) structure and function into a patient similarity network that predicted major adverse cardiac event(s) (MACE)...
Pattern Recognition, Automated Male Ventricular Function, Left Echocardiography Middle Aged Disease Progression Patient Readmission Ventricular Dysfunction, Left Retrospective Studies Unsupervised Machine Learning Image Interpretation, Computer-Assisted Humans Female Predictive Value of Tests Prospective Studies Aged Registries Prognosis Aged, 80 and over Adult
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Substrate Spatial Complexity Analysis for the Prediction of Ventricular Arrhythmias in Patients With Ischemic Cardiomyopathy.

Circulation. Arrhythmia and electrophysiology Mar 18, 2020
BACKGROUND: Transition zones between healthy myocardium and scar form a spatially complex substrate that may give rise to reentrant ventricular arrhythmias (VAs). We sought to assess the utility of a novel machine learning approach for quantifying 3-...
Fourier Analysis Gadolinium DTPA Death, Sudden, Cardiac Registries Arrhythmias, Cardiac Heart Rate Myocardial Ischemia Cardiomyopathies Stroke Volume Middle Aged Risk Assessment Diagnosis, Computer-Assisted Imaging, Three-Dimensional Female United States Risk Factors Contrast Media Aged Magnetic Resonance Imaging Humans Male Action Potentials Machine Learning Ventricular Function, Left Predictive Value of Tests Prognosis Retrospective Studies
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Prediction of prognosis in patients with tetralogy of Fallot based on deep learning imaging analysis.

Heart (British Cardiac Society) Mar 11, 2020
OBJECTIVE: To assess the utility of machine learning algorithms for automatically estimating prognosis in patients with repaired tetralogy of Fallot (ToF) using cardiac magnetic resonance (CMR).
Humans Prospective Studies Male Middle Aged Risk Assessment Diagnosis, Computer-Assisted Deep Learning Adolescent Prognosis Female Risk Factors Young Adult Adult Feasibility Studies Image Interpretation, Computer-Assisted Time Factors Germany Child Tetralogy of Fallot Electrocardiography Magnetic Resonance Imaging, Cine Predictive Value of Tests Registries
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Improving Mortality Predictions for Patients With Mechanical Circulatory Support Using Follow-Up Data and Machine Learning.

Circulation. Genomic and precision medicine Mar 11, 2020
Humans Machine Learning Prognosis Survival Rate Hospital Mortality Heart-Assist Devices Follow-Up Studies Registries Heart Failure
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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...
Plaque, Atherosclerotic Computed Tomography Angiography Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Registries Coronary Artery Disease Multidetector Computed Tomography Male Middle Aged Humans Diagnosis, Computer-Assisted Disease Progression Machine Learning Time Factors Prospective Studies Predictive Value of Tests Female Aged
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Evaluation of machine learning methods to stroke outcome prediction using a nationwide disease registry.

Computer methods and programs in biomedicine Feb 1, 2020
INTRODUCTION: Being able to predict functional outcomes after a stroke is highly desirable for clinicians. This allows clinicians to set reasonable goals with patients and relatives, and to reach shared after-care decisions for recovery or rehabilita...
Machine Learning Forecasting Female Aged Male Registries Stroke Physical Functional Performance Middle Aged Support Vector Machine Stroke Rehabilitation Taiwan Humans Outcome and Process Assessment, Health Care Neural Networks, Computer Artificial Intelligence
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Machine Learning Approach to Identify Stroke Within 4.5 Hours.

Stroke Jan 28, 2020
Background and Purpose- We aimed to investigate the ability of machine learning (ML) techniques analyzing diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging to identify patients within the reco...
Brain Ischemia Humans Middle Aged Models, Cardiovascular Machine Learning Diagnosis, Computer-Assisted Diffusion Magnetic Resonance Imaging Female Time Factors Aged Registries Male Stroke
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Validation of deep-learning image reconstruction for coronary computed tomography angiography: Impact on noise, image quality and diagnostic accuracy.

Journal of cardiovascular computed tomography Jan 13, 2020
BACKGROUND: Advances in image reconstruction are necessary to decrease radiation exposure from coronary CT angiography (CCTA) further, but iterative reconstruction has been shown to degrade image quality at high levels. Deep-learning image reconstruc...
Registries Coronary Artery Disease Humans Retrospective Studies Female Diagnosis, Computer-Assisted Reproducibility of Results Deep Learning Aged Artifacts Predictive Value of Tests Male Coronary Angiography Middle Aged Radiographic Image Interpretation, Computer-Assisted Coronary Vessels Computed Tomography Angiography
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