Matches in SemOpenAlex for { <https://semopenalex.org/work/W4387093889> ?p ?o ?g. }
Showing items 1 to 71 of
71
with 100 items per page.
- W4387093889 endingPage "105409" @default.
- W4387093889 startingPage "105409" @default.
- W4387093889 abstract "Cardiac morbidity like ischemic heart disease (IHD) causes global mortality. Diagnosis of IHD requires coronary angiograms — an invasive, sophisticated, and expensive procedure. However, non-invasive methods could not gain much confidence in swift diagnosis of IHD patients. These potential issues provided the research motivation for diagnosing IHD priorly in this pilot study. A computer-aided technique, as an alternate method to fasten and ease IHD detection and categorization, has been suggested in this cohort study. Here, the classification was conducted by a sandwich model of GRU and fuzzy logic in a deep GRU Fuzzy network. In this work, photoplethysmography (PPG) signals were acquired from 355 IHD patients. Gabor–Winger transform was used to derive signal features using statistical identities. Analysis was done with a Fuzzy GRU Network comprising GRU and BiGRU layers with fuzzy layers. An algorithm was designed with a Rete network and three membership functions to deduce fuzzy inference. Then, Choquet Integral was used for defuzzification. The proposed network predicted results with 0.85 accuracy, 0.86 recall, 0.84 precision, 0.86 sensitivity, 0.78 Micro-averaged F1-score, and 0.84 specificity. The network architecture was validated using ablation and comparative studies. The PRC and ROC curves gave the highest values of 0.91 AP and 0.90 AUC, respectively for this network. A state-of-the-art study was done to show the superiority of the technique. This computer-aided model using PPG might become a tool in predicting the type of therapy for IHD patients which will provide a non-invasive, inexpensive, and fast mode of diagnosis." @default.
- W4387093889 created "2023-09-28" @default.
- W4387093889 creator A5044064329 @default.
- W4387093889 creator A5047212453 @default.
- W4387093889 date "2024-01-01" @default.
- W4387093889 modified "2023-09-28" @default.
- W4387093889 title "Prediction of therapy for ischemic heart disease from PPG signals using fuzzy GRU network" @default.
- W4387093889 cites W1655097103 @default.
- W4387093889 cites W1982522576 @default.
- W4387093889 cites W1986417034 @default.
- W4387093889 cites W2007650547 @default.
- W4387093889 cites W2014311929 @default.
- W4387093889 cites W2051379371 @default.
- W4387093889 cites W2989675228 @default.
- W4387093889 cites W2999326224 @default.
- W4387093889 cites W3016569858 @default.
- W4387093889 cites W3091403751 @default.
- W4387093889 cites W3126652713 @default.
- W4387093889 cites W3166630818 @default.
- W4387093889 cites W3186679267 @default.
- W4387093889 cites W4226173998 @default.
- W4387093889 cites W4313201653 @default.
- W4387093889 cites W4380987424 @default.
- W4387093889 doi "https://doi.org/10.1016/j.bspc.2023.105409" @default.
- W4387093889 hasPublicationYear "2024" @default.
- W4387093889 type Work @default.
- W4387093889 citedByCount "0" @default.
- W4387093889 crossrefType "journal-article" @default.
- W4387093889 hasAuthorship W4387093889A5044064329 @default.
- W4387093889 hasAuthorship W4387093889A5047212453 @default.
- W4387093889 hasConcept C119857082 @default.
- W4387093889 hasConcept C126322002 @default.
- W4387093889 hasConcept C153180895 @default.
- W4387093889 hasConcept C154945302 @default.
- W4387093889 hasConcept C170260401 @default.
- W4387093889 hasConcept C1883856 @default.
- W4387093889 hasConcept C41008148 @default.
- W4387093889 hasConcept C42011625 @default.
- W4387093889 hasConcept C5274069 @default.
- W4387093889 hasConcept C58166 @default.
- W4387093889 hasConcept C71924100 @default.
- W4387093889 hasConceptScore W4387093889C119857082 @default.
- W4387093889 hasConceptScore W4387093889C126322002 @default.
- W4387093889 hasConceptScore W4387093889C153180895 @default.
- W4387093889 hasConceptScore W4387093889C154945302 @default.
- W4387093889 hasConceptScore W4387093889C170260401 @default.
- W4387093889 hasConceptScore W4387093889C1883856 @default.
- W4387093889 hasConceptScore W4387093889C41008148 @default.
- W4387093889 hasConceptScore W4387093889C42011625 @default.
- W4387093889 hasConceptScore W4387093889C5274069 @default.
- W4387093889 hasConceptScore W4387093889C58166 @default.
- W4387093889 hasConceptScore W4387093889C71924100 @default.
- W4387093889 hasLocation W43870938891 @default.
- W4387093889 hasOpenAccess W4387093889 @default.
- W4387093889 hasPrimaryLocation W43870938891 @default.
- W4387093889 hasRelatedWork W1767280227 @default.
- W4387093889 hasRelatedWork W2033914206 @default.
- W4387093889 hasRelatedWork W2042327336 @default.
- W4387093889 hasRelatedWork W2046077695 @default.
- W4387093889 hasRelatedWork W2133896845 @default.
- W4387093889 hasRelatedWork W2146076056 @default.
- W4387093889 hasRelatedWork W2163831990 @default.
- W4387093889 hasRelatedWork W2378160586 @default.
- W4387093889 hasRelatedWork W2996038082 @default.
- W4387093889 hasRelatedWork W3003836766 @default.
- W4387093889 hasVolume "87" @default.
- W4387093889 isParatext "false" @default.
- W4387093889 isRetracted "false" @default.
- W4387093889 workType "article" @default.