AIMC Topic: Heart Failure

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Diagnostic accuracy of artificial-intelligence-based electrocardiogram algorithm to estimate heart failure with reduced ejection fraction: A systematic review and meta-analysis.

Current problems in cardiology Feb 3, 2025
INTRODUCTION: AI-based ECG has shown good accuracy in diagnosing heart failure. However, due to the heterogeneity of studies regarding cutoff points, its precision for specifically detecting heart failure with left ventricle reduced ejection fraction...
Heart Failure Humans Artificial Intelligence Algorithms Ventricular Function, Left Stroke Volume Electrocardiography
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Machine learning-based risk prediction of mild cognitive impairment in patients with chronic heart failure: A model development and validation study.

Geriatric nursing (New York, N.Y.) Feb 1, 2025
Accurate identification of individuals at high risk for mild cognitive impairment (MCI) among chronic heart failure (CHF) patients is crucial for reducing rehospitalization and mortality rates. This study aimed to develop and validate a machine learn...
Risk Factors Aged Aged, 80 and over Cross-Sectional Studies Humans Machine Learning Female Male Middle Aged Risk Assessment Cognitive Dysfunction ROC Curve Nomograms Chronic Disease Heart Failure
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Chaotic gradient based optimization with fuzzy temporal optimized CNN for heart failure prediction.

Scientific reports Jan 31, 2025
Heart failure is a leading cause of premature death, especially among individuals with a sedentary lifestyle. Early and accurate detection is essential to prevent the progression of this situation. However, many existing prediction systems failed to ...
Algorithms Electronic Health Records Fuzzy Logic Heart Failure Humans Neural Networks, Computer Machine Learning
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Machine Learning-Based Risk Factor Analysis and Prediction Model Construction for the Occurrence of Chronic Heart Failure: Health Ecologic Study.

JMIR medical informatics Jan 31, 2025
BACKGROUND: Chronic heart failure (CHF) is a serious threat to human health, with high morbidity and mortality rates, imposing a heavy burden on the health care system and society. With the abundance of medical data and the rapid development of machi...
Humans Chronic Disease Aged Machine Learning Heart Failure Male Female Middle Aged Risk Factors Risk Assessment
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Prediction of mortality in heart failure by machine learning. Comparison with statistical modeling.

European journal of internal medicine Jan 28, 2025
BACKGROUND: Assessing the relative performance of machine learning (ML) methods and conventional statistical methods in predicting prognosis in heart failure (HF) still remains a challenging research field.
Prognosis Female Aged Male Humans Machine Learning Middle Aged Logistic Models Models, Statistical Heart Failure
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Health Care Professionals and Data Scientists' Perspectives on a Machine Learning System to Anticipate and Manage the Risk of Decompensation From Patients With Heart Failure: Qualitative Interview Study.

Journal of medical Internet research Jan 20, 2025
BACKGROUND: Heart failure (HF) is a significant global health problem, affecting approximately 64.34 million people worldwide. The worsening of HF, also known as HF decompensation, is a major factor behind hospitalizations, contributing to substantia...
Portugal Qualitative Research Interviews as Topic Data Science Heart Failure Humans Adult Machine Learning Male Health Personnel Middle Aged Female
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Survival parametric modeling for patients with heart failure based on Kernel learning.

BMC medical research methodology Jan 11, 2025
Time-to-event data are very common in medical applications. Regression models have been developed on such data especially in the field of survival analysis. Kernels are used to handle even more complicated and enormous quantities of medical data by i...
Humans Machine Learning Algorithms Models, Statistical Heart Failure Survival Analysis Proportional Hazards Models
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Multimodal deep learning for predicting in-hospital mortality in heart failure patients using longitudinal chest X-rays and electronic health records.

The international journal of cardiovascular imaging Jan 9, 2025
Amid an aging global population, heart failure has become a leading cause of hospitalization among older people. Its high prevalence and mortality rates underscore the importance of accurate mortality prediction for swift disease progression assessme...
Feasibility Studies Aged, 80 and over Heart Failure Male Radiography, Thoracic Middle Aged Deep Learning Risk Assessment Female Humans Time Factors Reproducibility of Results Decision Support Techniques Hospital Mortality Risk Factors Prognosis Predictive Value of Tests Aged Electronic Health Records
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Predicting 28-day all-cause mortality in patients admitted to intensive care units with pre-existing chronic heart failure using the stress hyperglycemia ratio: a machine learning-driven retrospective cohort analysis.

Cardiovascular diabetology Jan 8, 2025
Chronic heart failure (CHF) poses a significant threat to human health. The stress hyperglycemia ratio (SHR) is a novel metric for accurately assessing stress hyperglycemia, which has been correlated with adverse outcomes in various major diseases. H...
Time Factors Hyperglycemia Chronic Disease Predictive Value of Tests Male Middle Aged Risk Assessment Blood Glucose Cause of Death Heart Failure Patient Admission Biomarkers Prognosis Retrospective Studies Intensive Care Units Female Risk Factors Aged Aged, 80 and over Humans Machine Learning Decision Support Techniques Databases, Factual
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Clinical validation of an artificial intelligence-based decision support system for diagnosis and risk stratification of heart failure (STRATIFYHF): a protocol for a prospective, multicentre longitudinal study.

BMJ open Jan 7, 2025
INTRODUCTION: Heart failure (HF) is a complex clinical syndrome. Accurate risk stratification and early diagnosis of HF are challenging as its signs and symptoms are non-specific. We propose to address this global challenge by developing the STRATIFY...
Artificial Intelligence Prospective Studies Prognosis Female Humans Heart Failure Validation Studies as Topic Decision Support Systems, Clinical Longitudinal Studies Observational Studies as Topic Aged Multicenter Studies as Topic Male Middle Aged Risk Assessment
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