FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3048851138> ?p ?o ?g. }

• W3048851138 abstract "Background and Purpose: One-fifth of ischemic strokes are embolic strokes of undetermined source (ESUS). Their theoretical causes can be classified as cardioembolic versus noncardioembolic. This distinction has important implications, but the categories’ proportions are unknown. Methods: Using data from the Cornell Acute Stroke Academic Registry, we trained a machine-learning algorithm to distinguish cardioembolic versus non-cardioembolic strokes, then applied the algorithm to ESUS cases to determine the predicted proportion with an occult cardioembolic source. A panel of neurologists adjudicated stroke etiologies using standard criteria. We trained a machine learning classifier using data on demographics, comorbidities, vitals, laboratory results, and echocardiograms. An ensemble predictive method including L1 regularization, gradient-boosted decision tree ensemble (XGBoost), random forests, and multivariate adaptive splines was used. Random search and cross-validation were used to tune hyperparameters. Model performance was assessed using cross-validation among cases of known etiology. We applied the final algorithm to an independent set of ESUS cases to determine the predicted mechanism (cardioembolic or not). To assess our classifier’s validity, we correlated the predicted probability of a cardioembolic source with the eventual post-ESUS diagnosis of atrial fibrillation. Results: Among 1083 strokes with known etiologies, our classifier distinguished cardioembolic versus noncardioembolic cases with excellent accuracy (area under the curve, 0.85). Applied to 580 ESUS cases, the classifier predicted that 44% (95% credibility interval, 39%–49%) resulted from cardiac embolism. Individual ESUS patients’ predicted likelihood of cardiac embolism was associated with eventual atrial fibrillation detection (OR per 10% increase, 1.27 [95% CI, 1.03–1.57]; c-statistic, 0.68 [95% CI, 0.58–0.78]). ESUS patients with high predicted probability of cardiac embolism were older and had more coronary and peripheral vascular disease, lower ejection fractions, larger left atria, lower blood pressures, and higher creatinine levels. Conclusions: A machine learning estimator that distinguished known cardioembolic versus noncardioembolic strokes indirectly estimated that 44% of ESUS cases were cardioembolic." @default.
• W3048851138 created "2020-08-18" @default.
• W3048851138 creator A5002902942 @default.
• W3048851138 creator A5004953636 @default.
• W3048851138 creator A5021022648 @default.
• W3048851138 creator A5025877936 @default.
• W3048851138 creator A5031475597 @default.
• W3048851138 creator A5034330473 @default.
• W3048851138 creator A5046520659 @default.
• W3048851138 creator A5054660298 @default.
• W3048851138 creator A5054747839 @default.
• W3048851138 creator A5059916379 @default.
• W3048851138 creator A5064975333 @default.
• W3048851138 creator A5067166321 @default.
• W3048851138 creator A5084451114 @default.
• W3048851138 creator A5085675203 @default.
• W3048851138 creator A5091554389 @default.
• W3048851138 date "2020-09-01" @default.
• W3048851138 modified "2023-09-25" @default.
• W3048851138 title "Machine Learning Prediction of Stroke Mechanism in Embolic Strokes of Undetermined Source" @default.
• W3048851138 cites W1996490798 @default.
• W3048851138 cites W2002285876 @default.
• W3048851138 cites W2061546208 @default.
• W3048851138 cites W2067395123 @default.
• W3048851138 cites W2113315322 @default.
• W3048851138 cites W2116427214 @default.
• W3048851138 cites W2119972565 @default.
• W3048851138 cites W2125065061 @default.
• W3048851138 cites W2138595885 @default.
• W3048851138 cites W2150765167 @default.
• W3048851138 cites W2155690271 @default.
• W3048851138 cites W2285069016 @default.
• W3048851138 cites W2549334493 @default.
• W3048851138 cites W2591708623 @default.
• W3048851138 cites W2786615873 @default.
• W3048851138 cites W2803966697 @default.
• W3048851138 cites W2891629937 @default.
• W3048851138 cites W2922212575 @default.
• W3048851138 cites W2924498637 @default.
• W3048851138 cites W2926850141 @default.
• W3048851138 cites W2927941727 @default.
• W3048851138 cites W2939565435 @default.
• W3048851138 cites W2944133085 @default.
• W3048851138 cites W2945825099 @default.
• W3048851138 cites W2946228682 @default.
• W3048851138 cites W2966007257 @default.
• W3048851138 cites W2997156187 @default.
• W3048851138 cites W3035197101 @default.
• W3048851138 cites W4233056867 @default.
• W3048851138 doi "https://doi.org/10.1161/strokeaha.120.029305" @default.
• W3048851138 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8034802" @default.
• W3048851138 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32781943" @default.
• W3048851138 hasPublicationYear "2020" @default.
• W3048851138 type Work @default.
• W3048851138 sameAs 3048851138 @default.
• W3048851138 citedByCount "24" @default.
• W3048851138 countsByYear W30488511382020 @default.
• W3048851138 countsByYear W30488511382021 @default.
• W3048851138 countsByYear W30488511382022 @default.
• W3048851138 countsByYear W30488511382023 @default.
• W3048851138 crossrefType "journal-article" @default.
• W3048851138 hasAuthorship W3048851138A5002902942 @default.
• W3048851138 hasAuthorship W3048851138A5004953636 @default.
• W3048851138 hasAuthorship W3048851138A5021022648 @default.
• W3048851138 hasAuthorship W3048851138A5025877936 @default.
• W3048851138 hasAuthorship W3048851138A5031475597 @default.
• W3048851138 hasAuthorship W3048851138A5034330473 @default.
• W3048851138 hasAuthorship W3048851138A5046520659 @default.
• W3048851138 hasAuthorship W3048851138A5054660298 @default.
• W3048851138 hasAuthorship W3048851138A5054747839 @default.
• W3048851138 hasAuthorship W3048851138A5059916379 @default.
• W3048851138 hasAuthorship W3048851138A5064975333 @default.
• W3048851138 hasAuthorship W3048851138A5067166321 @default.
• W3048851138 hasAuthorship W3048851138A5084451114 @default.
• W3048851138 hasAuthorship W3048851138A5085675203 @default.
• W3048851138 hasAuthorship W3048851138A5091554389 @default.
• W3048851138 hasBestOaLocation W30488511381 @default.
• W3048851138 hasConcept C119857082 @default.
• W3048851138 hasConcept C126322002 @default.
• W3048851138 hasConcept C137627325 @default.
• W3048851138 hasConcept C154945302 @default.
• W3048851138 hasConcept C164705383 @default.
• W3048851138 hasConcept C2779161974 @default.
• W3048851138 hasConcept C2910003425 @default.
• W3048851138 hasConcept C3020199598 @default.
• W3048851138 hasConcept C41008148 @default.
• W3048851138 hasConcept C45942800 @default.
• W3048851138 hasConcept C541997718 @default.
• W3048851138 hasConcept C71924100 @default.
• W3048851138 hasConceptScore W3048851138C119857082 @default.
• W3048851138 hasConceptScore W3048851138C126322002 @default.
• W3048851138 hasConceptScore W3048851138C137627325 @default.
• W3048851138 hasConceptScore W3048851138C154945302 @default.
• W3048851138 hasConceptScore W3048851138C164705383 @default.
• W3048851138 hasConceptScore W3048851138C2779161974 @default.
• W3048851138 hasConceptScore W3048851138C2910003425 @default.
• W3048851138 hasConceptScore W3048851138C3020199598 @default.
• W3048851138 hasConceptScore W3048851138C41008148 @default.
• W3048851138 hasConceptScore W3048851138C45942800 @default.
• W3048851138 hasConceptScore W3048851138C541997718 @default.

• next