AIMC Topic: Asymptomatic Diseases

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Establishing a carotid artery stenosis disease cohort for comparative effectiveness research using natural language processing.

Journal of vascular surgery Jun 25, 2021
OBJECTIVE: Investigation of asymptomatic carotid stenosis treatment is hindered by the lack of a contemporary population-based disease cohort. We describe the use of natural language processing (NLP) to identify stenosis in patients undergoing caroti...
Computed Tomography Angiography Carotid Stenosis Comparative Effectiveness Research California International Classification of Diseases Magnetic Resonance Angiography Humans Medical Records Retrospective Studies Asymptomatic Diseases Cross-Sectional Studies Severity of Illness Index Hemodynamics Predictive Value of Tests Natural Language Processing Data Mining Ultrasonography, Doppler
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Cost Effectiveness of an Electrocardiographic Deep Learning Algorithm to Detect Asymptomatic Left Ventricular Dysfunction.

Mayo Clinic proceedings Jun 9, 2021
OBJECTIVE: To evaluate the cost-effectiveness of an artificial intelligence electrocardiogram (AI-ECG) algorithm under various clinical and cost scenarios when used for universal screening at age 65.
Humans Artificial Intelligence Algorithms Mass Screening Cost-Benefit Analysis Markov Chains Quality-Adjusted Life Years Ventricular Dysfunction, Left Asymptomatic Diseases Female Aged Male Middle Aged Deep Learning Electrocardiography
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Deep convolutional neural networks to predict cardiovascular risk from computed tomography.

Nature communications Jan 29, 2021
Coronary artery calcium is an accurate predictor of cardiovascular events. While it is visible on all computed tomography (CT) scans of the chest, this information is not routinely quantified as it requires expertise, time, and specialized equipment....
Humans Retrospective Studies Tomography, X-Ray Computed Female Reproducibility of Results Deep Learning Coronary Vessels Aged Image Processing, Computer-Assisted Asymptomatic Diseases Male Follow-Up Studies Cardiovascular Diseases Calcium Middle Aged Chest Pain Risk Assessment Heart Disease Risk Factors
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Association of a Serum Protein Signature With Rheumatoid Arthritis Development.

Arthritis & rheumatology (Hoboken, N.J.) Nov 10, 2020
OBJECTIVE: The pathophysiologic events that precede the onset of rheumatoid arthritis (RA) remain incompletely understood. This study was undertaken to identify changes in the serum proteome that precede the onset of RA, with the aim of providing new...
Adolescent Arthritis, Rheumatoid Proteomics Indians, North American Longitudinal Studies Anti-Citrullinated Protein Antibodies Young Adult Adult Male Middle Aged Disease Progression Ficolins Interleukin-1 Rheumatoid Factor Asymptomatic Diseases Lectins Calreticulin Toll-Like Receptor 2 Humans Machine Learning Tumor Necrosis Factor-alpha Female Aged
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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...
Peptide Fragments Heart Failure Ventricular Dysfunction, Left Natriuretic Peptide, Brain Asymptomatic Diseases Diastole Disease Progression Diagnosis, Computer-Assisted Deep Learning Cluster Analysis Ventricular Function, Left Humans Unsupervised Machine Learning Stroke Volume Biomarkers Predictive Value of Tests Echocardiography Retrospective Studies Middle Aged Female Risk Assessment Risk Factors Aged Aged, 80 and over Male
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Identifying prostate cancer and its clinical risk in asymptomatic men using machine learning of high dimensional peripheral blood flow cytometric natural killer cell subset phenotyping data.

eLife Jul 28, 2020
We demonstrate that prostate cancer can be identified by flow cytometric profiling of blood immune cell subsets. Herein, we profiled natural killer (NK) cell subsets in the blood of 72 asymptomatic men with Prostate-Specific Antigen (PSA) levels < 20...
Killer Cells, Natural Asymptomatic Diseases Blood Circulation Middle Aged Humans Diagnostic Techniques, Urological Risk Assessment Machine Learning Prostatic Neoplasms Aged Prostate-Specific Antigen Aged, 80 and over Flow Cytometry Male Practice Guidelines as Topic
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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...
Middle Aged Risk Assessment Deep Learning Adipose Tissue Predictive Value of Tests Coronary Angiography Coronary Artery Disease Coronary Vessels Vascular Calcification Asymptomatic Diseases Pericardium Tomography, X-Ray Computed Female Risk Factors Aged Aged, 80 and over Male Humans Prognosis
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ECG AI-Guided Screening for Low Ejection Fraction (EAGLE): Rationale and design of a pragmatic cluster randomized trial.

American heart journal Oct 25, 2019
BACKGROUND: A deep learning algorithm to detect low ejection fraction (EF) using routine 12-lead electrocardiogram (ECG) has recently been developed and validated. The algorithm was incorporated into the electronic health record (EHR) to automaticall...
Cost-Benefit Analysis Cardiac Output, Low Asymptomatic Diseases Echocardiography Deep Learning Humans Electrocardiography Artificial Intelligence Sample Size Prospective Studies Informed Consent Electronic Health Records Heart Failure
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Improving the clinical understanding of hypertrophic cardiomyopathy by combining patient data, machine learning and computer simulations: A case study.

Morphologie : bulletin de l'Association des anatomistes Sep 27, 2019
Most patients with hypertrophic cardiomyopathy (HCM), the most common genetic cardiac disease, remain asymptomatic, but others may suffer from sudden cardiac death. A better identification of those patients at risk, together with a better understandi...
Electrocardiography Magnetic Resonance Imaging Heart Ventricles Patient Selection Humans Models, Cardiovascular Machine Learning Cardiomyopathy, Hypertrophic Death, Sudden, Cardiac Computer Simulation Asymptomatic Diseases Clinical Decision-Making Risk Factors Risk Assessment
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Machine learning based risk prediction model for asymptomatic individuals who underwent coronary artery calcium score: Comparison with traditional risk prediction approaches.

Journal of cardiovascular computed tomography Sep 23, 2019
BACKGROUND: Machine learning (ML) is a computer algorithm used to identify patterns for prediction in various tasks, and ML methods have been beneficial for developing prediction models when applied to heterogeneous and large datasets. We aim to exam...
Middle Aged Humans Coronary Angiography Risk Assessment Retrospective Studies Registries Machine Learning Time Factors Republic of Korea Coronary Artery Disease Decision Support Techniques Health Status Female Vascular Calcification Databases, Factual Predictive Value of Tests Risk Factors Asymptomatic Diseases Prognosis Adult Male
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