FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2998894436> ?p ?o ?g. }

• W2998894436 abstract "Abstract Funding Acknowledgements Bay Labs, Inc; San Francisco, CA Background/Introduction: When used by experienced examiners, the utility of point-of-care (POC) ultrasound for assessing cardiac anatomy and function has been well established. However, in some clinical circumstances (Primary Care offices, Intensive Care Unit, some Emergency Rooms, or in remote settings) in which a rapid assessment of cardiac anatomy and dynamics can facilitate patient care, an examiner experienced at POC scanning may not be immediately available. Purpose To help novice users acquire clinically useful standard cardiac views using novel machine learning (ML) software. Methods We used an investigational device that employs ML software to provide real-time adaptive guidance of transducer position and orientation to help novice users acquire tomographic views of the heart. We tested the utility of this approach when 4 nurses with no prior training in sonography performed POC studies on 16 subjects (10 healthy, 6 with cardiac abnormalities; 9 men; body mass index normal in 6, overweight in 6, and obese in 4 subjects). Each nurse underwent didactic training and 4 hours of supervised practice using the ML program. Each nurse scanned each study subject using a scanner equipped with ML software to acquire 10 digital two-dimensional image clips, including: parasternal long axis, short axis at the aortic valve, mitral valve, and mid-left ventricle (LV), apical 2-, 4-, and 5-chamber, subcostal 4-chamber, and longitudinal views of the inferior vena cava (IVC). All video clips (n = 640) were later reviewed independently by 5 level 3-trained cardiologists who were blinded to subject, scanner, and each others assessments. The expert readers reviewed each set of 10 clips to determine if the following variables could be assessed qualitatively: LV size and function; right ventricular (RV) size and function; aortic, mitral and tricuspid valves; pericardial effusion; left atrial size; IVC size. Results The majority of expert readers concurred, independently, that the sets of images acquired by nurses using ML guidance allowed qualitative assessment of LV size and function in 98%, pericardial effusion in 98%, RV size and function in 92%, and aortic and mitral valve anatomy and dynamics in 94-97% of cases. Qualitative assessment of LA size was feasible in 95%. Images of the IVC were judged as adequate for assessment in 58%. Conclusion This preliminary study suggests the potential value of novel ML software by demonstrating that nurses with limited training can acquire tomographic images useful for qualitative assessment of the cardiac chambers and valves in more than 90% of the subjects examined. This approach might be useful when timely POC cardiac assessment is indicated in settings where an experienced examiner is not available. Further refinements in the guiding software are needed to improve the success rate of IVC imaging, since IVC size can be a useful indicator of volume status." @default.
• W2998894436 created "2020-01-23" @default.
• W2998894436 creator A5002407127 @default.
• W2998894436 creator A5002727452 @default.
• W2998894436 creator A5002939213 @default.
• W2998894436 creator A5003431369 @default.
• W2998894436 creator A5004858136 @default.
• W2998894436 creator A5022538261 @default.
• W2998894436 creator A5025404272 @default.
• W2998894436 creator A5036427123 @default.
• W2998894436 creator A5045174287 @default.
• W2998894436 creator A5051271923 @default.
• W2998894436 creator A5053296604 @default.
• W2998894436 creator A5056991193 @default.
• W2998894436 creator A5062994447 @default.
• W2998894436 creator A5064763704 @default.
• W2998894436 date "2020-01-01" @default.
• W2998894436 modified "2023-10-12" @default.
• W2998894436 title "547 Point-of-care cardiac assessment using machine learning to guide image acquisition" @default.
• W2998894436 doi "https://doi.org/10.1093/ehjci/jez319.281" @default.
• W2998894436 hasPublicationYear "2020" @default.
• W2998894436 type Work @default.
• W2998894436 sameAs 2998894436 @default.
• W2998894436 citedByCount "2" @default.
• W2998894436 countsByYear W29988944362021 @default.
• W2998894436 countsByYear W29988944362023 @default.
• W2998894436 crossrefType "journal-article" @default.
• W2998894436 hasAuthorship W2998894436A5002407127 @default.
• W2998894436 hasAuthorship W2998894436A5002727452 @default.
• W2998894436 hasAuthorship W2998894436A5002939213 @default.
• W2998894436 hasAuthorship W2998894436A5003431369 @default.
• W2998894436 hasAuthorship W2998894436A5004858136 @default.
• W2998894436 hasAuthorship W2998894436A5022538261 @default.
• W2998894436 hasAuthorship W2998894436A5025404272 @default.
• W2998894436 hasAuthorship W2998894436A5036427123 @default.
• W2998894436 hasAuthorship W2998894436A5045174287 @default.
• W2998894436 hasAuthorship W2998894436A5051271923 @default.
• W2998894436 hasAuthorship W2998894436A5053296604 @default.
• W2998894436 hasAuthorship W2998894436A5056991193 @default.
• W2998894436 hasAuthorship W2998894436A5062994447 @default.
• W2998894436 hasAuthorship W2998894436A5064763704 @default.
• W2998894436 hasBestOaLocation W29988944361 @default.
• W2998894436 hasConcept C126838900 @default.
• W2998894436 hasConcept C141071460 @default.
• W2998894436 hasConcept C143753070 @default.
• W2998894436 hasConcept C19527891 @default.
• W2998894436 hasConcept C23036609 @default.
• W2998894436 hasConcept C2778739407 @default.
• W2998894436 hasConcept C2778789114 @default.
• W2998894436 hasConcept C2910216633 @default.
• W2998894436 hasConcept C2910830941 @default.
• W2998894436 hasConcept C71924100 @default.
• W2998894436 hasConceptScore W2998894436C126838900 @default.
• W2998894436 hasConceptScore W2998894436C141071460 @default.
• W2998894436 hasConceptScore W2998894436C143753070 @default.
• W2998894436 hasConceptScore W2998894436C19527891 @default.
• W2998894436 hasConceptScore W2998894436C23036609 @default.
• W2998894436 hasConceptScore W2998894436C2778739407 @default.
• W2998894436 hasConceptScore W2998894436C2778789114 @default.
• W2998894436 hasConceptScore W2998894436C2910216633 @default.
• W2998894436 hasConceptScore W2998894436C2910830941 @default.
• W2998894436 hasConceptScore W2998894436C71924100 @default.
• W2998894436 hasIssue "Supplement_1" @default.
• W2998894436 hasLocation W29988944361 @default.
• W2998894436 hasOpenAccess W2998894436 @default.
• W2998894436 hasPrimaryLocation W29988944361 @default.
• W2998894436 hasRelatedWork W2007358753 @default.
• W2998894436 hasRelatedWork W2065407334 @default.
• W2998894436 hasRelatedWork W2109510943 @default.
• W2998894436 hasRelatedWork W2122691768 @default.
• W2998894436 hasRelatedWork W2365162211 @default.
• W2998894436 hasRelatedWork W2374634788 @default.
• W2998894436 hasRelatedWork W2474447826 @default.
• W2998894436 hasRelatedWork W4304474375 @default.
• W2998894436 hasRelatedWork W4313379795 @default.
• W2998894436 hasRelatedWork W48426095 @default.
• W2998894436 hasVolume "21" @default.
• W2998894436 isParatext "false" @default.
• W2998894436 isRetracted "false" @default.
• W2998894436 magId "2998894436" @default.
• W2998894436 workType "article" @default.