Matches in SemOpenAlex for { <https://semopenalex.org/work/W4380795364> ?p ?o ?g. }
Showing items 1 to 70 of
70
with 100 items per page.
- W4380795364 abstract "Objectives: To assess whether electrocardiography (ECG)-based artificial intelligence (AI) algorithm developed to detect 1-year mortality in patients with HF with reduced ejection fraction (HFrEF). Methods and results: Data from two hospital visits (2016 Oct to 2021 Apr) was used. Participants with good quality baseline ECGs and HFrEF were included. We tested the hypothesis that the application of AI to the ECG could identify 1-yr mortality in HFrEF patients. A total of 16,228 (64% male, mean age of 58.5) were eligible. When tested on an independent set of 16,228 patients, the network model yielded values for the area under the curve, sensitivity, specificity, and accuracy of 0.83, 83.3%, and 64.2%, respectively ( Figure a ). Those with a positive AI screen were at 2.6 times the risk (p<0.0001) of developing future mortality compared with those with a negative screen ( Figure b ). We used a sensitivity map to visualize the ECG region used in the AI model to detect high 1-yr mortality in HFrEF ( Figure c ). The map shows that the AI model focused on the QRS complex, particularly the R-wave, in most patients. Conclusions: The application of AI to the ECG permits the ECG to serve as a powerful screening tool for detecting 1-yr mortality in HFrEF. Figure a. The area under the curve of the convolutional neural network used to identify 1-year mortality of heart failure with reduced ejection fraction. Figure b. Long-term incidence of mortality in patients with initially 1-year mortality stratified by artificial intelligence classification. Figure c. Sensitivity map of a deep learning model for detecting 1-year mortality in heart failure with reduced ejection fraction." @default.
- W4380795364 created "2023-06-16" @default.
- W4380795364 creator A5009171643 @default.
- W4380795364 creator A5010093998 @default.
- W4380795364 creator A5021596397 @default.
- W4380795364 creator A5028902149 @default.
- W4380795364 creator A5038172025 @default.
- W4380795364 creator A5062643671 @default.
- W4380795364 creator A5072156399 @default.
- W4380795364 date "2022-11-08" @default.
- W4380795364 modified "2023-09-25" @default.
- W4380795364 title "Abstract 13550: Electrocardiographic-Based Artificial Intelligence Model in Prediction of 1-year Mortality in Heart Failure With Reduced Ejection Fraction" @default.
- W4380795364 doi "https://doi.org/10.1161/circ.146.suppl_1.13550" @default.
- W4380795364 hasPublicationYear "2022" @default.
- W4380795364 type Work @default.
- W4380795364 citedByCount "0" @default.
- W4380795364 crossrefType "journal-article" @default.
- W4380795364 hasAuthorship W4380795364A5009171643 @default.
- W4380795364 hasAuthorship W4380795364A5010093998 @default.
- W4380795364 hasAuthorship W4380795364A5021596397 @default.
- W4380795364 hasAuthorship W4380795364A5028902149 @default.
- W4380795364 hasAuthorship W4380795364A5038172025 @default.
- W4380795364 hasAuthorship W4380795364A5062643671 @default.
- W4380795364 hasAuthorship W4380795364A5072156399 @default.
- W4380795364 hasConcept C111773187 @default.
- W4380795364 hasConcept C119857082 @default.
- W4380795364 hasConcept C126322002 @default.
- W4380795364 hasConcept C154945302 @default.
- W4380795364 hasConcept C164705383 @default.
- W4380795364 hasConcept C2778198053 @default.
- W4380795364 hasConcept C2780040984 @default.
- W4380795364 hasConcept C41008148 @default.
- W4380795364 hasConcept C50644808 @default.
- W4380795364 hasConcept C58471807 @default.
- W4380795364 hasConcept C71924100 @default.
- W4380795364 hasConcept C76318530 @default.
- W4380795364 hasConcept C78085059 @default.
- W4380795364 hasConcept C81363708 @default.
- W4380795364 hasConceptScore W4380795364C111773187 @default.
- W4380795364 hasConceptScore W4380795364C119857082 @default.
- W4380795364 hasConceptScore W4380795364C126322002 @default.
- W4380795364 hasConceptScore W4380795364C154945302 @default.
- W4380795364 hasConceptScore W4380795364C164705383 @default.
- W4380795364 hasConceptScore W4380795364C2778198053 @default.
- W4380795364 hasConceptScore W4380795364C2780040984 @default.
- W4380795364 hasConceptScore W4380795364C41008148 @default.
- W4380795364 hasConceptScore W4380795364C50644808 @default.
- W4380795364 hasConceptScore W4380795364C58471807 @default.
- W4380795364 hasConceptScore W4380795364C71924100 @default.
- W4380795364 hasConceptScore W4380795364C76318530 @default.
- W4380795364 hasConceptScore W4380795364C78085059 @default.
- W4380795364 hasConceptScore W4380795364C81363708 @default.
- W4380795364 hasIssue "Suppl_1" @default.
- W4380795364 hasLocation W43807953641 @default.
- W4380795364 hasOpenAccess W4380795364 @default.
- W4380795364 hasPrimaryLocation W43807953641 @default.
- W4380795364 hasRelatedWork W187959415 @default.
- W4380795364 hasRelatedWork W2055573102 @default.
- W4380795364 hasRelatedWork W2067643107 @default.
- W4380795364 hasRelatedWork W2110628407 @default.
- W4380795364 hasRelatedWork W2351455450 @default.
- W4380795364 hasRelatedWork W2362265450 @default.
- W4380795364 hasRelatedWork W2369801253 @default.
- W4380795364 hasRelatedWork W2587323853 @default.
- W4380795364 hasRelatedWork W4315784592 @default.
- W4380795364 hasRelatedWork W2461862799 @default.
- W4380795364 hasVolume "146" @default.
- W4380795364 isParatext "false" @default.
- W4380795364 isRetracted "false" @default.
- W4380795364 workType "article" @default.