AIMC Topic: Heart Failure

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The effect of principal component analysis in the diagnosis of congestive heart failure via heart rate variability analysis.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
In this study, we investigated the effect of principal component analysis (PCA) in congestive heart failure (CHF) diagnosis using various machine learning algorithms from 5-min HRV data. The extracted 59 heart rate variability (HRV) features consist ...

Deep-Learning-Based Color Doppler Ultrasound Image Feature in the Diagnosis of Elderly Patients with Chronic Heart Failure Complicated with Sarcopenia.

Journal of healthcare engineering
The neural network algorithm of deep learning was applied to optimize and improve color Doppler ultrasound images, which was used for the research on elderly patients with chronic heart failure (CHF) complicated with sarcopenia, so as to analyze the ...

Importance of Preserved Tricuspid Valve Function for Effective Soft Robotic Augmentation of the Right Ventricle in Cases of Elevated Pulmonary Artery Pressure.

Cardiovascular engineering and technology
PURPOSE: In clinical practice, many patients with right heart failure (RHF) have elevated pulmonary artery pressures and increased afterload on the right ventricle (RV). In this study, we evaluated the feasibility of RV augmentation using a soft robo...

Predicting survival in heart failure: a risk score based on machine-learning and change point algorithm.

Clinical research in cardiology : official journal of the German Cardiac Society
OBJECTIVE: Machine learning (ML) algorithm can improve risk prediction because ML can select features and segment continuous variables effectively unbiased. We generated a risk score model for mortality with ML algorithms in East-Asian patients with ...

Sex Differences in the Association Between Inflammation and Event-Free Survival in Patients With Heart Failure.

The Journal of cardiovascular nursing
BACKGROUND: Heart failure (HF) is associated with chronic inflammation, which is adversely associated with survival. Although sex-related differences in inflammation have been described in patients with HF, whether sex-related differences in inflamma...

Prediction Model Using Machine Learning for Mortality in Patients with Heart Failure.

The American journal of cardiology
Heart Failure (HF) is a major cause of morbidity and mortality in the US. With aging of the US population, the public health burden of HF is enormous. We aimed to develop an ensemble prediction model for 30-day mortality after discharge using machine...

Time-frequency time-space long short-term memory networks for image classification of histopathological tissue.

Scientific reports
Image analysis in histopathology provides insights into the microscopic examination of tissue for disease diagnosis, prognosis, and biomarker discovery. Particularly for cancer research, precise classification of histopathological images is the ultim...

Decoding empagliflozin's molecular mechanism of action in heart failure with preserved ejection fraction using artificial intelligence.

Scientific reports
The use of sodium-glucose co-transporter 2 inhibitors to treat heart failure with preserved ejection fraction (HFpEF) is under investigation in ongoing clinical trials, but the exact mechanism of action is unclear. Here we aimed to use artificial int...

Machine ​learning algorithms for claims data-based prediction of in-hospital mortality in patients with heart failure.

ESC heart failure
AIMS: Models predicting mortality in heart failure (HF) patients are often limited with regard to performance and applicability. The aim of this study was to develop a reliable algorithm to compute expected in-hospital mortality rates in HF cohorts o...