FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3216049288> ?p ?o ?g. }

• W3216049288 endingPage "15" @default.
• W3216049288 startingPage "1" @default.
• W3216049288 abstract "Myocardial infarction (MI) causes rapid and permanent damage to the heart muscle. Without timely diagnosis and treatment, it will deteriorate the myocardial structure and function. The precise localization of MI based on 12-lead electrocardiogram (ECG) signals still remains a great challenge. We, thus, present a novel algorithm for automatically localizing MI from multilead ECG signals. The image-based heartbeat tensorization establishes a third-order lead <inline-formula> <tex-math notation=LaTeX>${times }$ </tex-math></inline-formula> time <inline-formula> <tex-math notation=LaTeX>${times }$ </tex-math></inline-formula> amplitude tensor structure. This image tensor encompasses key information between leads and the correlation within the heartbeat, which are essential for the MI diagnosis. The Tucker2 decomposition-based feature extractor automatically extracts the morphological core tensor of the image tensor. The morphological core tensor includes crucial information among three dimensions. Localization of MI is evaluated as a multiclass problem. We use the bagged decision tree for multiclass classification. The 12-lead ECG signals from the benchmark Physikalisch-Technische Bundesanstalt (PTB) database are employed to verify the applicability of the proposed algorithm. The PTB database includes normal ECG, 11 types of MI: anterior, anterior lateral, anterior septal, anterior septal lateral, inferior, inferior lateral, inferior posterior, inferior posterior lateral, lateral, posterior, and posterior lateral. We demonstrated, with the morphological core features obtained from the image tensor, that 12 categories of ECG signals achieved a total accuracy of 99.67&#x0025; and an F1 score of 0.9997. The area under the receiver operating characteristic curves and precision-recall curves of each kind of ECG signal has been found to be more than 0.88. The proposed algorithm effectively realizes the classification of normal ECG and 11 categories of MI, and our approach of using a 12-lead ECG signal herein holds great promise for helping the cardiologists localize MI." @default.
• W3216049288 created "2021-12-06" @default.
• W3216049288 creator A5006890334 @default.
• W3216049288 creator A5009770501 @default.
• W3216049288 creator A5011611619 @default.
• W3216049288 creator A5019056174 @default.
• W3216049288 creator A5019653584 @default.
• W3216049288 creator A5069849278 @default.
• W3216049288 creator A5079018005 @default.
• W3216049288 creator A5082706113 @default.
• W3216049288 date "2022-01-01" @default.
• W3216049288 modified "2023-10-18" @default.
• W3216049288 title "Automated Localization of Myocardial Infarction of Image-Based Multilead ECG Tensor With Tucker2 Decomposition" @default.
• W3216049288 cites W1473944704 @default.
• W3216049288 cites W1963826206 @default.
• W3216049288 cites W1970158471 @default.
• W3216049288 cites W1971983548 @default.
• W3216049288 cites W1972003923 @default.
• W3216049288 cites W1991042426 @default.
• W3216049288 cites W2022691337 @default.
• W3216049288 cites W2024165284 @default.
• W3216049288 cites W2025603201 @default.
• W3216049288 cites W2041110545 @default.
• W3216049288 cites W2047181473 @default.
• W3216049288 cites W2061185532 @default.
• W3216049288 cites W2091076299 @default.
• W3216049288 cites W2092647425 @default.
• W3216049288 cites W2162273778 @default.
• W3216049288 cites W2162800060 @default.
• W3216049288 cites W2219972493 @default.
• W3216049288 cites W2251133041 @default.
• W3216049288 cites W2469230926 @default.
• W3216049288 cites W2495557304 @default.
• W3216049288 cites W2512426799 @default.
• W3216049288 cites W2702116941 @default.
• W3216049288 cites W2765350348 @default.
• W3216049288 cites W2767583913 @default.
• W3216049288 cites W2775521641 @default.
• W3216049288 cites W2791509447 @default.
• W3216049288 cites W2796148034 @default.
• W3216049288 cites W2804642894 @default.
• W3216049288 cites W2907328574 @default.
• W3216049288 cites W2914231497 @default.
• W3216049288 cites W2924456201 @default.
• W3216049288 cites W2928448622 @default.
• W3216049288 cites W2943642020 @default.
• W3216049288 cites W2947860185 @default.
• W3216049288 cites W2963184634 @default.
• W3216049288 cites W2977515051 @default.
• W3216049288 cites W2978767476 @default.
• W3216049288 cites W2980825080 @default.
• W3216049288 cites W2993687209 @default.
• W3216049288 cites W2994951659 @default.
• W3216049288 cites W3006339384 @default.
• W3216049288 cites W3012684726 @default.
• W3216049288 cites W3103507112 @default.
• W3216049288 cites W3107063238 @default.
• W3216049288 cites W4214806317 @default.
• W3216049288 doi "https://doi.org/10.1109/tim.2021.3104394" @default.
• W3216049288 hasPublicationYear "2022" @default.
• W3216049288 type Work @default.
• W3216049288 sameAs 3216049288 @default.
• W3216049288 citedByCount "2" @default.
• W3216049288 countsByYear W32160492882023 @default.
• W3216049288 crossrefType "journal-article" @default.
• W3216049288 hasAuthorship W3216049288A5006890334 @default.
• W3216049288 hasAuthorship W3216049288A5009770501 @default.
• W3216049288 hasAuthorship W3216049288A5011611619 @default.
• W3216049288 hasAuthorship W3216049288A5019056174 @default.
• W3216049288 hasAuthorship W3216049288A5019653584 @default.
• W3216049288 hasAuthorship W3216049288A5069849278 @default.
• W3216049288 hasAuthorship W3216049288A5079018005 @default.
• W3216049288 hasAuthorship W3216049288A5082706113 @default.
• W3216049288 hasConcept C13852961 @default.
• W3216049288 hasConcept C138885662 @default.
• W3216049288 hasConcept C153180895 @default.
• W3216049288 hasConcept C154945302 @default.
• W3216049288 hasConcept C155281189 @default.
• W3216049288 hasConcept C2524010 @default.
• W3216049288 hasConcept C2776401178 @default.
• W3216049288 hasConcept C33923547 @default.
• W3216049288 hasConcept C38652104 @default.
• W3216049288 hasConcept C41008148 @default.
• W3216049288 hasConcept C41895202 @default.
• W3216049288 hasConcept C52622490 @default.
• W3216049288 hasConceptScore W3216049288C13852961 @default.
• W3216049288 hasConceptScore W3216049288C138885662 @default.
• W3216049288 hasConceptScore W3216049288C153180895 @default.
• W3216049288 hasConceptScore W3216049288C154945302 @default.
• W3216049288 hasConceptScore W3216049288C155281189 @default.
• W3216049288 hasConceptScore W3216049288C2524010 @default.
• W3216049288 hasConceptScore W3216049288C2776401178 @default.
• W3216049288 hasConceptScore W3216049288C33923547 @default.
• W3216049288 hasConceptScore W3216049288C38652104 @default.
• W3216049288 hasConceptScore W3216049288C41008148 @default.
• W3216049288 hasConceptScore W3216049288C41895202 @default.
• W3216049288 hasConceptScore W3216049288C52622490 @default.
• W3216049288 hasFunder F4320321001 @default.

• next