Rickey E. Carter

Jul 12, 2024 | nature.com | Rickey E. Carter |David Kaye |M. Louis Handoko |Ryan J. Tedford |Mads J. Andersen |Frederik H. Verbrugge

AbstractHeart failure with preserved ejection fraction (HFpEF) is under-recognized in clinical practice. Although a previously developed risk score, termed H2FPEF, can be used to estimate HFpEF probability, this score requires imaging data, which is often unavailable. Here we sought to develop an HFpEF screening model that is based exclusively on clinical variables and that can guide the need for echocardiography and further testing.

May 18, 2024 | medrxiv.org | Quigly Dragotakes |David Sullivan |Rickey E. Carter |Michael Joyner

The authors have declared no competing interest. This study did not receive any fundingI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Apr 23, 2024 | ukexportnews.co.uk | Rickey E. Carter

On recent revisits to two Steelcoat 100/400 System applications in the Northeast of England, Winn & Coales (Denso) Ltd. were proud to confirm that both applications were performing as expected The Steelcoat 100/400 System applications were providing exemplary protection from corrosion over a decade since their installations.

Feb 19, 2024 | ukexportnews.co.uk | Rickey E. Carter

At Winn & Coales (Denso), it’s extremely important to us that our customers feel confident in applying our corrosion prevention and sealing systems Ensuring the longevity and cost-effectiveness of every application begins with helping our customers select the most suitable Denso™ products for their individual project requirements, along with offering free product application training that’s available throughout the UK and beyond.

Jan 5, 2024 | nature.com | Eunjung Lee |Paul Friedman |Rickey E. Carter |Barry A. Borlaug |Zachi I. Attia

AbstractAssessment of left ventricular diastolic function plays a major role in the diagnosis and prognosis of cardiac diseases, including heart failure with preserved ejection fraction. We aimed to develop an artificial intelligence (AI)-enabled electrocardiogram (ECG) model to identify echocardiographically determined diastolic dysfunction and increased filling pressure.