Article

Multimodal Artificial Intelligence Approaches for the Diagnosis and Understanding of Heart Failure: A Contemporary Review

2026-08-14

Abstract excerpt

<h4>Purpose: </h4> of Review: Heart failure affects over 64 million people worldwide, yet diagnosis remains challenging, with nearly two-thirds of cases estimated to remain undiagnosed overall. This review synthesises current evidence on multimodal artificial intelligence (AI) for heart failure detection, covering fusion strategies, explainability, and implementation challenges. Recent Findings: Unimodal AI achiev...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: e325f0ad-ea16-562f-a3cd-8f4694d0beda
DOI: 10.20944/preprints202608.1013.v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Multimodal Artificial Intelligence Approaches for the Diagnosis and Understanding of Heart Failure: A Contemporary ReviewDOI 10.20944/preprints202608.1013.v1Read

Integrating multimodal intelligence in heart failure: AI-driven risk prediction, precision diagnosis, phenotyping, personalized treatment, and prognosis.Semantic proximity Read

Artificial intelligence and heart failure: A state-of-the-art review.Semantic proximity Read

Composite Artificial Intelligence–Enabled Electrocardiogram for Detection and Prediction of Structural Heart DiseaseSemantic proximity Read

An Artificial Intelligence Model for Detection of Heart Failure with Preserved Ejection Fraction: A Report from HeartShare StudySemantic proximity Read

Advances in Interpretation of Electrocardiogram by Artificial IntelligenceSemantic proximity Read

Echocardiography-Based, Artificial Intelligence-Enabled Electrocardiography (AI-ECG) for Diastolic Hemodynamics Phenotyping in Acute Heart Failure (AHF)Semantic proximity Read

Artificial Intelligence-Enabled Electrocardiogram for Elevated Left Ventricular Filling PressureSemantic proximity Read

Explainable Artificial Intelligence for the Detection and Characterisation of Stage B Heart FailureSemantic proximity Read

Artificial Intelligence-Enhanced Electrocardiogram Models for Detection of Left Ventricular Dysfunction: A Comparison StudySemantic proximity Read

Phenotypic Selectivity of Artificial Intelligence-enhanced Electrocardiography in Cardiovascular Diagnosis and Risk PredictionSemantic proximity Read

Artificial intelligence–enabled electrocardiogram for mortality and cardiovascular risk estimation: An actionable, explainable and biologically plausible platformSemantic proximity Read

Artificial Intelligence in Cardiac Amyloidosis: A State-of-the-Art ReviewSemantic proximity Read