<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Campbell RT</submitter><funding>British Heart Foundation</funding><funding>Roche Diagnostics</funding><funding>AstraZeneca</funding><pagination>3401-3410</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12803686</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>27(12)</volume><pubmed_abstract>&lt;h4>Aims&lt;/h4>Echocardiography is a rate-limiting step in the timely diagnosis of heart failure (HF). Automated reporting of echocardiograms has the potential to streamline workflow. The aim of this study was to test the diagnostic accuracy of fully automated artificial intelligence (AI) analysis of images acquired using handheld echocardiography and its interchangeability with expert human-analysed cart-based echocardiograms in a real-world cohort with suspected HF.&lt;h4>Methods and results&lt;/h4>In this multicentre, prospective, observational study, patients with suspected HF had two echocardiograms: one handheld portable and one cart-based scan. Both echocardiograms were analysed using fully automated AI software and by human expert sonographers. The primary endpoint was the diagnostic accur</pubmed_abstract><journal>European journal of heart failure</journal><pubmed_title>Artificial intelligence fully automated analysis of handheld echocardiography in real-world patients with suspected heart failure.</pubmed_title><pmcid>PMC12803686</pmcid><funding_grant_id>RE/18/6/34217</funding_grant_id><pubmed_authors>Nordin S</pubmed_authors><pubmed_authors>McKinley G</pubmed_authors><pubmed_authors>Murphy CL</pubmed_authors><pubmed_authors>Campbell RT</pubmed_authors><pubmed_authors>Macklin L</pubmed_authors><pubmed_authors>McConnachie A</pubmed_authors><pubmed_authors>Taylor K</pubmed_authors><pubmed_authors>Turnbull P</pubmed_authors><pubmed_authors>Taylor-Sweet D</pubmed_authors><pubmed_authors>McIntyre A</pubmed_authors><pubmed_authors>Lam CSP</pubmed_authors><pubmed_authors>Lee MMY</pubmed_authors><pubmed_authors>Brooksbank KJM</pubmed_authors><pubmed_authors>Osmanska J</pubmed_authors><pubmed_authors>McDowell K</pubmed_authors><pubmed_authors>Sonecki P</pubmed_authors><pubmed_authors>Hainey H</pubmed_authors><pubmed_authors>McMurray JJV</pubmed_authors><pubmed_authors>Butler E</pubmed_authors><pubmed_authors>Jarvie J</pubmed_authors><pubmed_authors>Lowe DJ</pubmed_authors><pubmed_authors>Curtain JP</pubmed_authors><pubmed_authors>Petrie MC</pubmed_authors><pubmed_authors>Mangion K</pubmed_authors><pubmed_authors>Hartshorne-Evans N</pubmed_authors><pubmed_authors>Graham FJ</pubmed_authors><pubmed_authors>Docherty KF</pubmed_authors><pubmed_authors>Pellicori P</pubmed_authors><pubmed_authors>Simpson J</pubmed_authors><pubmed_authors>Welsh P</pubmed_authors><pubmed_authors>Adamson C</pubmed_authors><pubmed_authors>McCoubrey A</pubmed_authors><pubmed_authors>Haig C</pubmed_authors></additional><is_claimable>false</is_claimable><name>Artificial intelligence fully automated analysis of handheld echocardiography in real-world patients with suspected heart failure.</name><description>&lt;h4>Aims&lt;/h4>Echocardiography is a rate-limiting step in the timely diagnosis of heart failure (HF). Automated reporting of echocardiograms has the potential to streamline workflow. The aim of this study was to test the diagnostic accuracy of fully automated artificial intelligence (AI) analysis of images acquired using handheld echocardiography and its interchangeability with expert human-analysed cart-based echocardiograms in a real-world cohort with suspected HF.&lt;h4>Methods and results&lt;/h4>In this multicentre, prospective, observational study, patients with suspected HF had two echocardiograms: one handheld portable and one cart-based scan. Both echocardiograms were analysed using fully automated AI software and by human expert sonographers. The primary endpoint was the diagnostic accur</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Dec</publication><modification>2026-06-06T14:57:17.137Z</modification><creation>2026-06-01T03:07:40.638Z</creation></dates><accession>S-EPMC12803686</accession><cross_references><pubmed>40702880</pubmed><doi>10.1002/ejhf.3783</doi></cross_references></HashMap>