AIMC Topic: Cardiovascular Diseases

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Proteomics-Enabled Deep Learning Machine Algorithms Can Enhance Prediction of Mortality.

Journal of the American College of Cardiology Oct 19, 2021
BACKGROUND: Individualized risk prediction represents a prerequisite for providing personalized medicine.
Risk Assessment Deep Learning Cohort Studies Proteomics Follow-Up Studies Aged Male Cardiovascular Diseases Middle Aged Models, Cardiovascular Neural Networks, Computer Algorithms Female Humans
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Machine learning approaches improve risk stratification for secondary cardiovascular disease prevention in multiethnic patients.

Open heart Oct 1, 2021
OBJECTIVES: Identifying high-risk patients is crucial for effective cardiovascular disease (CVD) prevention. It is not known whether electronic health record (EHR)-based machine-learning (ML) models can improve CVD risk stratification compared with a...
Humans Machine Learning Retrospective Studies Electronic Health Records Female Incidence Time Factors United States Follow-Up Studies Male Ethnicity Risk Factors Cardiovascular Diseases Aged Middle Aged Aged, 80 and over Risk Assessment Survival Rate
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Predicting cardiac adverse events in patients receiving immune checkpoint inhibitors: a machine learning approach.

Journal for immunotherapy of cancer Oct 1, 2021
BACKGROUND: Treatment with immune checkpoint inhibitors (ICIs) has been associated with an increased rate of cardiac events. There are limited data on the risk factors that predict cardiac events in patients treated with ICIs. Therefore, we created a...
Aged Male Cardiovascular Diseases Middle Aged Immune Checkpoint Inhibitors Humans Machine Learning Female
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Cause-specific mortality prediction in older residents of São Paulo, Brazil: a machine learning approach.

Age and ageing Sep 11, 2021
BACKGROUND: Populational ageing has been increasing in a remarkable rate in developing countries. In this scenario, preventive strategies could help to decrease the burden of higher demands for healthcare services. Machine learning algorithms have be...
Humans Machine Learning Algorithms Aged Cardiovascular Diseases Brazil Cause of Death
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Combining digital data and artificial intelligence for cardiovascular health.

Cardiovascular research Jul 27, 2021
Physical Fitness Cardiorespiratory Fitness Fitness Trackers Risk Reduction Behavior Mobile Applications Humans Predictive Value of Tests Healthy Lifestyle Health Status Remote Sensing Technology Artificial Intelligence Telemedicine Cardiovascular Diseases Smartphone
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Cardiovascular RNA markers and artificial intelligence may improve COVID-19 outcome: a position paper from the EU-CardioRNA COST Action CA17129.

Cardiovascular research Jul 7, 2021
The coronavirus disease 2019 (COVID-19) pandemic has been as unprecedented as unexpected, affecting more than 105 million people worldwide as of 8 February 2020 and causing more than 2.3 million deaths according to the World Health Organization (WHO)...
Cardiovascular System SARS-CoV-2 Artificial Intelligence Cardiovascular Diseases COVID-19 Quality of Life Biomarkers RNA Humans
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Joint Associations of Multiple Dietary Components With Cardiovascular Disease Risk: A Machine-Learning Approach.

American journal of epidemiology Jul 1, 2021
The human diet consists of a complex mixture of components. To realistically assess dietary impacts on health, new statistical tools that can better address nonlinear, collinear, and interactive relationships are necessary. Using data from 1,928 heal...
Diet Surveys Follow-Up Studies Bayes Theorem Heart Disease Risk Factors Linear Models Female Adult Male Cardiovascular Diseases Risk Assessment United States Longitudinal Studies Humans Middle Aged Machine Learning Diet Prospective Studies
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Deep-learning-based cardiovascular risk stratification using coronary artery calcium scores predicted from retinal photographs.

The Lancet. Digital health May 1, 2021
BACKGROUND: Coronary artery calcium (CAC) score is a clinically validated marker of cardiovascular disease risk. We developed and validated a novel cardiovascular risk stratification system based on deep-learning-predicted CAC from retinal photograph...
Predictive Value of Tests Area Under Curve Singapore Coronary Artery Disease Proportional Hazards Models Humans Kaplan-Meier Estimate Algorithms Vascular Calcification Republic of Korea Retina Female Middle Aged Aged United Kingdom Risk Assessment Adult Deep Learning Male ROC Curve Cardiovascular Diseases
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Current trends in the use of machine learning for diagnostics and/or risk stratification in cardiovascular disease.

Cardiovascular research Apr 23, 2021
Clinical Decision-Making Reproducibility of Results Cardiac Imaging Techniques Risk Factors Humans Risk Assessment Artificial Intelligence Diagnosis, Computer-Assisted Cardiovascular Diseases Prognosis Predictive Value of Tests Image Interpretation, Computer-Assisted
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A comparison of general and disease-specific machine learning models for the prediction of unplanned hospital readmissions.

Journal of the American Medical Informatics Association : JAMIA Mar 18, 2021
Unplanned hospital readmissions are a burden to patients and increase healthcare costs. A wide variety of machine learning (ML) models have been suggested to predict unplanned hospital readmissions. These ML models were often specifically trained on ...
Datasets as Topic Neoplasms Female Humans Cohort Studies Chronic Disease Hospitalization Machine Learning Tertiary Care Centers Treatment Outcome Area Under Curve Male Prognosis Lung Diseases Models, Statistical Cardiovascular Diseases Electronic Health Records Patient Readmission
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