FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3112720625> ?p ?o ?g. }

• W3112720625 abstract "The outcome of cardiopulmonary resuscitation (CPR) depends on timely recognition of the underlying cause of cardiac arrest. Ventricular fibrillation (VF) waveform analysis to differentiate primary VF from secondary asphyxia-associated VF may allow tailoring of therapies to improve cardiac arrest outcomes. Therefore, the primary goal of this investigation was to develop a novel technique utilizing wavelet synchrosqueezed transform (WSST) and decision-tree classifier that was specifically adapted to discriminate between these two incidents of VF.Secondary analytical investigation of electrocardiography (ECG) data obtained from swine models of either primary VF (n=18) or secondary asphyxia-associated VF (7min of asphyxia prior to VF induction; n=12). In the primary analysis, WSST technique was applied to the first 35s of the VF ECG signal to identify the most differentiating characteristics of the signal for use as features to develop a machine learning algorithm to classify the arrest as either primary VF vs. secondary asphyxia-associated VF. The performance of this new interactive Machine Learning algorithm with Wavelet Energy features of ECG (MLWAVE) was assessed using both classification accuracy and area under the receiver operating characteristic curve (AUCROC). To evaluate the validity of the new technique, the amplitude spectrum area (AMSA)-based technique, a well-established defibrillation classification method, was also applied to the same ECG signals. The classification accuracy and AUCROC were then compared between the two techniques.For the primary analysis evaluating the first 35s of the VF waveform, the MLWAVE technique classified the type of VF with high accuracy (28/28 [100%], AUCROC: 1.00). The MLWAVE technique performed better than the AMSA technique across all comparisons, but given the small sample sizes, differences were not statistically significant (accuracy: 100% vs. 85.7%; p=0.24; AUCROC: 1.00 vs. 0.82; p=0.24).This analytical investigation illustrates the advantages of the MLWAVE signal processing method which was associated with 100% accuracy in classifying the type of VF waveform: primary vs. asphyxia-associated. Such classification could lead to personalized tailoring of resuscitation (e.g., immediate defibrillation vs. continued CPR and treatment of reversible cardiac arrest causes before defibrillation) to improve outcomes for cardiac arrest." @default.
• W3112720625 created "2020-12-21" @default.
• W3112720625 creator A5023592446 @default.
• W3112720625 creator A5030549451 @default.
• W3112720625 creator A5031954544 @default.
• W3112720625 creator A5033636865 @default.
• W3112720625 creator A5038937500 @default.
• W3112720625 creator A5055520900 @default.
• W3112720625 creator A5058693463 @default.
• W3112720625 creator A5088418140 @default.
• W3112720625 date "2021-03-01" @default.
• W3112720625 modified "2023-10-16" @default.
• W3112720625 title "MLWAVE: A novel algorithm to classify primary versus secondary asphyxia-associated ventricular fibrillation" @default.
• W3112720625 cites W1981280082 @default.
• W3112720625 cites W1981728478 @default.
• W3112720625 cites W1982184914 @default.
• W3112720625 cites W2006617902 @default.
• W3112720625 cites W2014337138 @default.
• W3112720625 cites W2019647222 @default.
• W3112720625 cites W2023568873 @default.
• W3112720625 cites W2035668031 @default.
• W3112720625 cites W2035993163 @default.
• W3112720625 cites W2039086947 @default.
• W3112720625 cites W2042293855 @default.
• W3112720625 cites W2051212900 @default.
• W3112720625 cites W2054878302 @default.
• W3112720625 cites W2056346922 @default.
• W3112720625 cites W2096758262 @default.
• W3112720625 cites W2105981176 @default.
• W3112720625 cites W2113062770 @default.
• W3112720625 cites W2116179239 @default.
• W3112720625 cites W2142709672 @default.
• W3112720625 cites W2143462490 @default.
• W3112720625 cites W2165948365 @default.
• W3112720625 cites W2299335913 @default.
• W3112720625 cites W2328176404 @default.
• W3112720625 cites W2461593239 @default.
• W3112720625 cites W2467158638 @default.
• W3112720625 cites W2560661011 @default.
• W3112720625 cites W2598818939 @default.
• W3112720625 cites W2747275622 @default.
• W3112720625 cites W2754703823 @default.
• W3112720625 cites W2795854105 @default.
• W3112720625 cites W2957140299 @default.
• W3112720625 cites W2995473105 @default.
• W3112720625 cites W3026205973 @default.
• W3112720625 cites W4300192115 @default.
• W3112720625 doi "https://doi.org/10.1016/j.resplu.2020.100052" @default.
• W3112720625 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7869586" @default.
• W3112720625 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33569548" @default.
• W3112720625 hasPublicationYear "2021" @default.
• W3112720625 type Work @default.
• W3112720625 sameAs 3112720625 @default.
• W3112720625 citedByCount "0" @default.
• W3112720625 crossrefType "journal-article" @default.
• W3112720625 hasAuthorship W3112720625A5023592446 @default.
• W3112720625 hasAuthorship W3112720625A5030549451 @default.
• W3112720625 hasAuthorship W3112720625A5031954544 @default.
• W3112720625 hasAuthorship W3112720625A5033636865 @default.
• W3112720625 hasAuthorship W3112720625A5038937500 @default.
• W3112720625 hasAuthorship W3112720625A5055520900 @default.
• W3112720625 hasAuthorship W3112720625A5058693463 @default.
• W3112720625 hasAuthorship W3112720625A5088418140 @default.
• W3112720625 hasBestOaLocation W31127206251 @default.
• W3112720625 hasConcept C11413529 @default.
• W3112720625 hasConcept C119857082 @default.
• W3112720625 hasConcept C126322002 @default.
• W3112720625 hasConcept C153180895 @default.
• W3112720625 hasConcept C154945302 @default.
• W3112720625 hasConcept C164705383 @default.
• W3112720625 hasConcept C197424946 @default.
• W3112720625 hasConcept C2777055891 @default.
• W3112720625 hasConcept C2777795826 @default.
• W3112720625 hasConcept C2778165595 @default.
• W3112720625 hasConcept C2779914510 @default.
• W3112720625 hasConcept C2781005686 @default.
• W3112720625 hasConcept C41008148 @default.
• W3112720625 hasConcept C42219234 @default.
• W3112720625 hasConcept C47432892 @default.
• W3112720625 hasConcept C554190296 @default.
• W3112720625 hasConcept C58471807 @default.
• W3112720625 hasConcept C71924100 @default.
• W3112720625 hasConcept C76155785 @default.
• W3112720625 hasConceptScore W3112720625C11413529 @default.
• W3112720625 hasConceptScore W3112720625C119857082 @default.
• W3112720625 hasConceptScore W3112720625C126322002 @default.
• W3112720625 hasConceptScore W3112720625C153180895 @default.
• W3112720625 hasConceptScore W3112720625C154945302 @default.
• W3112720625 hasConceptScore W3112720625C164705383 @default.
• W3112720625 hasConceptScore W3112720625C197424946 @default.
• W3112720625 hasConceptScore W3112720625C2777055891 @default.
• W3112720625 hasConceptScore W3112720625C2777795826 @default.
• W3112720625 hasConceptScore W3112720625C2778165595 @default.
• W3112720625 hasConceptScore W3112720625C2779914510 @default.
• W3112720625 hasConceptScore W3112720625C2781005686 @default.
• W3112720625 hasConceptScore W3112720625C41008148 @default.
• W3112720625 hasConceptScore W3112720625C42219234 @default.
• W3112720625 hasConceptScore W3112720625C47432892 @default.
• W3112720625 hasConceptScore W3112720625C554190296 @default.
• W3112720625 hasConceptScore W3112720625C58471807 @default.

• next