AIMC Topic: Heart Failure

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A Machine Learning-derived Risk Score Improves Prediction of Outcomes After LVAD Implantation: An Analysis of the INTERMACS Database.

Journal of cardiac failure Oct 31, 2024
BACKGROUND: Significant variability in outcomes after left ventricular assist device (LVAD) implantation emphasize the importance of accurately assessing patients' risk before surgery. This study assesses the Machine Learning Assessment of Risk and E...
Hospital Mortality Treatment Outcome Predictive Value of Tests Registries Male Middle Aged Risk Assessment Heart Failure Heart-Assist Devices Machine Learning Databases, Factual Prognosis Retrospective Studies Female Risk Factors Humans Aged
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Electrocardiograph analysis for risk assessment of heart failure with preserved ejection fraction: A deep learning model.

ESC heart failure Oct 27, 2024
AIMS: Heart failure with preserved ejection fraction (HFpEF) requires an efficient screening method. We developed a deep learning model (DLM) to screen HFpEF risk using electrocardiograms (ECGs).
Deep Learning Electrocardiography Heart Failure Stroke Volume Middle Aged Risk Assessment Humans Prospective Studies Female Aged Male Ventricular Function, Left
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Automated Identification of Heart Failure With Reduced Ejection Fraction Using Deep Learning-Based Natural Language Processing.

JACC. Heart failure Oct 23, 2024
BACKGROUND: The lack of automated tools for measuring care quality limits the implementation of a national program to assess guideline-directed care in heart failure with reduced ejection fraction (HFrEF).
Humans Female Aged Aged, 80 and over Male Deep Learning Stroke Volume Natural Language Processing Echocardiography Patient Discharge Middle Aged Heart Failure
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Noninvasive biometric monitoring technologies for patients with heart failure.

Heart failure reviews Oct 22, 2024
Heart failure remains one of the leading causes of mortality and hospitalizations in the US that not only impacts quality of life but also poses a significant public health burden. The majority of affected patients are admitted with signs and symptom...
Monitoring, Physiologic Heart Failure Humans Telemedicine Biometry Quality of Life
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ChatGPT-4 extraction of heart failure symptoms and signs from electronic health records.

Progress in cardiovascular diseases Oct 21, 2024
BACKGROUND: Natural language processing (NLP) can facilitate research utilizing data from electronic health records (EHRs). Large language models can potentially improve NLP applications leveraging EHR notes. The objective of this study was to assess...
Data Mining Symptom Assessment United States Predictive Value of Tests Natural Language Processing Heart Failure Humans Machine Learning Electronic Health Records
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A machine learning tool for identifying newly diagnosed heart failure in individuals with known diabetes in primary care.

ESC heart failure Oct 20, 2024
AIMS: We aimed to create a predictive model utilizing machine learning (ML) to identify new cases of congestive heart failure (CHF) in individuals with diabetes in primary health care (PHC) through the analysis of diagnostic data.
Humans Risk Factors Aged Adult Male Machine Learning Retrospective Studies Female Diabetes Mellitus Follow-Up Studies Heart Failure Middle Aged Case-Control Studies Primary Health Care
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Utilizing echocardiography and unsupervised machine learning for heart failure risk identification.

International journal of cardiology Oct 10, 2024
BACKGROUND: Global longitudinal strain (GLS) is recognized as a powerful predictor of heart failure (HF). However, the entire strain curve may entail important prognostic information regarding HF risk that might be undiscovered by only focusing on th...
Heart Failure Risk Assessment Follow-Up Studies Unsupervised Machine Learning Humans Adult Female Male Aged Echocardiography Middle Aged
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Machine learning in the prevention of heart failure.

Heart failure reviews Oct 7, 2024
Heart failure (HF) is a global pandemic with a growing prevalence and is a growing burden on the healthcare system. Machine learning (ML) has the potential to revolutionize medicine and can be applied in many different forms to aid in the prevention ...
Heart Failure Humans Machine Learning Risk Assessment
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Deep Learning-based 12-Lead Electrocardiogram for Low Left Ventricular Ejection Fraction Detection in Patients.

The Canadian journal of cardiology Sep 27, 2024
BACKGROUND: Reduced left ventricular ejection fraction (LVEF) initiates heart failure, and promptly identifying low ejection fraction is crucial for managing progression and averting mortality. In this study we developed an artificial intelligence-en...
Middle Aged Deep Learning Electrocardiography Aged Follow-Up Studies Humans Male Heart Failure Algorithms Ventricular Function, Left Ventricular Dysfunction, Left Female Stroke Volume
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Explainable machine learning and online calculators to predict heart failure mortality in intensive care units.

ESC heart failure Sep 19, 2024
AIMS: This study aims to develop explainable machine learning models and clinical tools for predicting mortality in patients in the intensive care unit (ICU) with heart failure (HF).
Intensive Care Units Humans Hospital Mortality Female Male Machine Learning Aged Middle Aged Nomograms Prognosis Survival Rate Risk Assessment Follow-Up Studies Retrospective Studies Heart Failure
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