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Related Concept Videos

Heart Failure IV: Classification and Diagnostic Evaluation01:30

Heart Failure IV: Classification and Diagnostic Evaluation

27
Heart failure can be classified in various ways, with the most common classifications based on physical activity limitations, disease progression, severity, and treatment strategies.The Functional Classification of Heart Failure divides patients into four categories based on physical activity limitation due to symptom burden.Class I: Patients in this class have cardiac disease but no physical activity limitations. Ordinary activities like walking, climbing stairs, or routine tasks do not cause...
27
Heart Failure VI: Adjunct Therapies01:22

Heart Failure VI: Adjunct Therapies

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Additional therapies for treating patients with heart failure (HF) may include procedural interventions, supplemental oxygen, the management of sleep disorders, and nutritional therapy.Procedural InterventionsImplantable Cardioverter-Defibrillator: For patients at risk of life-threatening arrhythmias due to severe left ventricular dysfunction, an Implantable Cardioverter-Defibrillator (ICD) can detect and terminate these arrhythmias, preventing sudden cardiac death and improving survival rates.
25
Heart Failure V: Medical Management01:30

Heart Failure V: Medical Management

19
Medical Management of Acute Decompensated Heart Failure (ADHF)The primary goals of therapy for patients hospitalized with acute decompensated heart failure (ADHF) include:Relieving symptomsOptimizing volume statusSupporting oxygenation and ventilationMaintaining cardiac output (CO) and end-organ perfusionIdentifying and addressing the cause of ADHFPreventing complicationsProviding patient education on factors precipitating HF exacerbationPlanning for dischargeOngoing monitoring and assessment...
19
Heart Failure II: Pathophysiology01:29

Heart Failure II: Pathophysiology

31
Systolic Heart Failure and Compensatory MechanismsSystolic heart failure (also termed HFrEF, Heart Failure with Reduced Ejection Fraction) is the most prevalent type of heart filure. It results in a decreased volume of blood being pumped from the ventricle. The aortic arch and carotid sinuses have baroreceptors that detect reduced blood pressure, triggering the sympathetic nervous system (SNS) to release epinephrine and norepinephrine. Initially, this response aims to boost heart rate and...
31
Heart Failure Drugs: Inhibitors of Renin-Angiotensin System01:26

Heart Failure Drugs: Inhibitors of Renin-Angiotensin System

488
The activation of the sympathetic nervous system and the renin-angiotensin-aldosterone system (RAAS) contributes to cardiac remodeling, and inhibiting the RAAS is a pharmacological target in heart failure management. As a result, neurohumoral modulation is a crucial treatment principle for managing heart failure. This approach involves using medications like ACE inhibitors (ACEIs), angiotensin receptor blockers (ARBs), β-blockers, mineralocorticoid receptor antagonists (MRAs), and neutral...
488
Pathophysiology of Heart Failure01:17

Pathophysiology of Heart Failure

1.8K
Heart failure (HF) is a progressive syndrome involving ventricles that leads to inadequate cardiac output. It can be classified based on location and output or ejection fraction. Ejection fraction (EF) is an essential measurement in the diagnosis and surveillance of HF. Reduced EF corresponds to systolic heart failure (HFrEF). However, HF with preserved ejection fraction (HFpEF) is becoming increasingly prevalent. Also known as diastolic HF, this form of HF is related to aging. The...
1.8K

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Updated: Aug 26, 2025

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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Identifying potential candidates for advanced heart failure therapies using an interpretable machine learning

Heming Yao1, Jessica R Golbus2, Jonathan Gryak3

  • 1Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan.

The Journal of Heart and Lung Transplantation : the Official Publication of the International Society for Heart Transplantation
|October 3, 2022
PubMed
Summary
This summary is machine-generated.

A new machine learning model helps identify heart failure patients needing advanced therapy evaluation. This system integrates clinical knowledge to improve timely access to treatments like heart transplantation and VADs.

Keywords:
heart failure advanced therapiesheart transplantationleft ventricular assist devicemachine learningmechanical circulatory support

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Area of Science:

  • Cardiology
  • Artificial Intelligence
  • Health Informatics

Background:

  • Systemic barriers impede timely access to advanced heart failure therapies, including heart transplantation and left ventricular assist devices.
  • Automated systems are needed to assist clinicians in evaluating heart failure patients for advanced therapies at optimal times.

Purpose of the Study:

  • To develop and validate a novel machine learning model for identifying heart failure patients who require evaluation for advanced therapies.

Main Methods:

  • A retrospective study utilized data from the REVIVAL and INTERMACS registries.
  • A machine learning model was developed using tropical geometry and fuzzy logic principles, incorporating clinician knowledge for accessible recommendations.
  • The model was trained and validated on data from 4,694 heart failure patients.

Main Results:

  • The model, when informed by expert clinical knowledge, achieved an F1 score of 43.8%, recall of 51.1%, and precision of 46.9%.
  • Performance was comparable to existing machine learning models.
  • The model generated 11 transparent and parsimonious clinical rules, outperforming other rule-generating models.

Conclusions:

  • A machine learning model was successfully trained to identify advanced heart failure patients needing evaluation for advanced therapies.
  • The model's methodology, which incorporates clinical knowledge for accessible recommendations, has potential applications beyond heart failure care.