AIMC Topic: Heart Failure

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Digital Solutions in HF Education: What Can Patients and Clinicians Gain?

Current heart failure reports
PURPOSE OF REVIEW: Heart failure (HF) imposes an expanding global health burden, necessitating innovative approaches to education for both patients and clinicians. This review evaluates the evolving landscape of digital health tools in HF education a...

Evaluation of the DAMSUN-HF trial: the role of an artificial intelligence stethoscope in detecting reduced ejection fraction in patients living in a low-resource region.

Heart failure reviews
Evaluation of ejection fraction (EF) is paramount for patients with symptoms of heart failure. While transthoracic echocardiography (TTE) is the most common way to evaluate EF, recent advances in artificial intelligence (AI) have opened the door for ...

Multimodal Data-Driven Explainable Prognostic Model for Major Adverse Cardiovascular Events Prediction in Patients With Unstable Angina and Heart Failure With Preserved Ejection Fraction: Multicenter, Cross-Regional Cohort Study.

Journal of medical Internet research
BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) and unstable angina (UA) often coexist in clinical practice, constituting a high-risk cardiovascular phenotype with a markedly increased incidence of major adverse cardiovascular even...

Ultrasound as the New Stethoscope: A Journey From Just Locating Fluid to Assessing Haemodynamics and Venous Congestion.

British journal of hospital medicine (London, England : 2005)
Point-of-care ultrasound (POCUS) has evolved from a simple tool for fluid localization to a comprehensive modality for hemodynamic assessment and real-time clinical decision-making. The Bedside Lung Ultrasound in Emergency (BLUE) protocol enables cli...

Non-Invasive Remote Monitoring in Heart Failure: Towards Wearable Devices and Artificial Intelligence Solutions : Short Title: Remote Monitoring and Wearable Devices in Heart Failure.

Current heart failure reports
PURPOSE OF REVIEW: This review examines the potential benefits of non-invasive remote monitoring in patients with heart failure (HF), focusing on early detection of clinical deterioration and reducing hospitalizations. Key questions addressed include...

Predicting 30-Days Hospital Readmission for Patients with Heart Failure Using Electronic Health Record Embeddings: Comparative Evaluation.

JMIR medical informatics
BACKGROUND: Heart failure (HF) is a public health concern with a wider impact on quality of life and cost of care. One of the major challenges in HF is the higher rate of unplanned readmissions and suboptimal performance of models to predict the read...

HearteXplain: explainable prediction of acute heart failure and identification of hematologic biomarkers using EBMs and Morris sensitivity analysis.

Scientific reports
Hematological biomarkers have emerged as powerful tools in diagnosing Acute Heart Failure (AHF). This study introduces a novel diagnostic framework that integrates Explainable Artificial Intelligence (XAI) with Morris Sensitivity Analysis (MSA) to en...

Predicting 30-day and 1-year mortality in heart failure with preserved ejection fraction (HFpEF).

PloS one
OBJECTIVES: To develop and compare prediction models for 30-day and 1-year mortality in Heart failure with preserved ejection fraction (HFpEF) using EHR data, utilizing both traditional and machine learning (ML) techniques.

AI-based approach for heart failure readmission prediction using SCG, ECG, and GSR signals.

Physiological measurement
Heart failure (HF) is considered a global pandemic because of increasing prevalence, high mortality rate, frequent hospitalization, and associated economic burden. This study explores a noninvasive method that may help in managing HF patients by pred...

Detection of Hypokalemia, Hyponatremia, and Hyperkalemia in Heart Failure Patients Using Artificial Intelligence Techniques via Electrocardiography.

Turk Kardiyoloji Dernegi arsivi : Turk Kardiyoloji Derneginin yayin organidir
OBJECTIVE: Detection and monitoring of electrolyte imbalances are essential for the appropriate treatment of many metabolic diseases. However, no reliable and noninvasive tool currently exists for such detection. Electrolyte disorders, particularly i...