AIMC Topic: Heart Failure

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Definition and Validation of Prognostic Phenotypes in Moderate Aortic Stenosis.

JACC. Cardiovascular imaging Aug 14, 2024
BACKGROUND: Adverse outcomes from moderate aortic stenosis (AS) may be caused by progression to severe AS or by the effects of comorbidities. In the absence of randomized trial evidence favoring aortic valve replacement (AVR) in patients with moderat...
Phenotype Prognosis Female Reproducibility of Results Risk Factors Humans Cluster Analysis Aortic Valve Stenosis Aortic Valve Unsupervised Machine Learning Predictive Value of Tests Heart Failure Aged Aged, 80 and over Male Echocardiography Middle Aged Risk Assessment Comorbidity Severity of Illness Index Time Factors
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Characterization of cardiac resynchronization therapy response through machine learning and personalized models.

Computers in biology and medicine Aug 13, 2024
INTRODUCTION: The characterization and selection of heart failure (HF) patients for cardiac resynchronization therapy (CRT) remain challenging, with around 30% non-responder rate despite following current guidelines. This study aims to propose a nove...
Heart Failure Cardiac Resynchronization Therapy Models, Cardiovascular Female Aged Male Middle Aged Humans Machine Learning Precision Medicine
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Use of artificial intelligence-guided echocardiography to detect cardiac dysfunction and heart valve disease in rural and remote areas: Rationale and design of the AGILE-echo trial.

American heart journal Aug 10, 2024
BACKGROUND: Transthoracic echocardiography (TTE) is essential in the diagnosis of cardiovascular diseases (CVD), including but not limited to heart failure (HF) and heart valve disease (HVD). However, its dependence on expert acquisition means that i...
Humans Artificial Intelligence Middle Aged Rural Population Australia Heart Failure Heart Valve Diseases Female Aged Male Echocardiography
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Comparison of machine learning and conventional statistical modeling for predicting readmission following acute heart failure hospitalization.

American heart journal Jul 31, 2024
INTRODUCTION: Developing accurate models for predicting the risk of 30-day readmission is a major healthcare interest. Evidence suggests that models developed using machine learning (ML) may have better discrimination than conventional statistical mo...
Humans Machine Learning Retrospective Studies Male Acute Disease Female Middle Aged Heart Failure Hospitalization Risk Assessment Patient Readmission Aged Ontario Aged, 80 and over Models, Statistical
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SHAP based predictive modeling for 1 year all-cause readmission risk in elderly heart failure patients: feature selection and model interpretation.

Scientific reports Jul 31, 2024
Heart failure (HF) is a significant global public health concern with a high readmission rate, posing a serious threat to the health of the elderly population. While several studies have used machine learning (ML) to develop all-cause readmission ris...
Heart Failure Patient Readmission Aged, 80 and over Male Risk Assessment Machine Learning ROC Curve Retrospective Studies Female Risk Factors Humans Aged
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Multimodal deep learning models utilizing chest X-ray and electronic health record data for predictive screening of acute heart failure in emergency department.

Computer methods and programs in biomedicine Jul 29, 2024
BACKGROUND AND OBJECTIVES: Ambiguity in diagnosing acute heart failure (AHF) leads to inappropriate treatment and potential side effects of rescue medications. To address this issue, this study aimed to use multimodality deep learning models combinin...
Emergency Service, Hospital Male Middle Aged Natriuretic Peptide, Brain Humans Acute Disease Deep Learning Radiography, Thoracic Peptide Fragments Electronic Health Records ROC Curve Heart Failure Female Aged
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Prediction of Left Ventricle Pressure Indices Via a Machine Learning Approach Combining ECG, Pulse Oximetry, and Cardiac Sounds: a Preclinical Feasibility Study.

Journal of cardiovascular translational research Jul 17, 2024
Heart failure (HF) is defined as the inability of the heart to meet body oxygen demand requiring an elevation in left ventricular filling pressures (LVP) to compensate. LVP increase can be assessed in the cardiac catheterization laboratory, but this ...
Machine Learning Heart Failure Heart Rate Oximetry Swine, Miniature Heart Sounds Phonocardiography Ventricular Pressure Electrocardiography Disease Models, Animal Predictive Value of Tests Signal Processing, Computer-Assisted Animals Feasibility Studies Ventricular Function, Left Stroke Volume Swine
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Deep learning for predicting rehospitalization in acute heart failure: Model foundation and external validation.

ESC heart failure Jul 9, 2024
AIMS: Assessing the risk for HF rehospitalization is important for managing and treating patients with HF. To address this need, various risk prediction models have been developed. However, none of them used deep learning methods with real-world data...
Follow-Up Studies Acute Disease Heart Failure Patient Readmission Male Middle Aged Risk Assessment Deep Learning Retrospective Studies Female Risk Factors Aged Humans Prognosis
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Deep learning prediction of survival in patients with heart failure using chest radiographs.

The international journal of cardiovascular imaging Jul 5, 2024
Heart failure (HF) is associated with high rates of morbidity and mortality. The value of deep learning survival prediction models using chest radiographs in patients with heart failure is currently unclear. The aim of our study is to develop and val...
Humans Decision Support Techniques Predictive Value of Tests Prognosis Reproducibility of Results Retrospective Studies Heart Failure Risk Factors Female Radiography, Thoracic Aged Aged, 80 and over Male Middle Aged Risk Assessment Deep Learning Time Factors
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Screening of Secretory Proteins Linking Major Depressive Disorder with Heart Failure Based on Comprehensive Bioinformatics Analysis and Machine Learning.

Biomolecules Jul 4, 2024
BACKGROUND: Major depressive disorder (MDD) plays a crucial role in the occurrence of heart failure (HF). This investigation was undertaken to explore the possible mechanism of MDD's involvement in HF pathogenesis and identify candidate biomarkers fo...
Animals Depressive Disorder, Major Genome-Wide Association Study Protein Interaction Maps Mice Computational Biology Mendelian Randomization Analysis Heart Failure Humans Machine Learning Biomarkers
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