FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4280630103> ?p ?o ?g. }

• W4280630103 endingPage "1247" @default.
• W4280630103 startingPage "1247" @default.
• W4280630103 abstract "Background This study aims to explore a deep learning (DL) algorithm for developing a prognostic model and perform survival analyses in SBT patients. Methods The demographic and clinical features of patients with SBTs were extracted from the Surveillance, Epidemiology and End Results (SEER) database. We randomly split the samples into the training set and the validation set at 7:3. Cox proportional hazards (Cox-PH) analysis and the DeepSurv algorithm were used to develop models. The performance of the Cox-PH and DeepSurv models was evaluated using receiver operating characteristic curves, calibration curves, C-statistics and decision-curve analysis (DCA). A Kaplan−Meier (K−M) survival analysis was performed for further explanation on prognostic effect of the Cox-PH model. Results The multivariate analysis demonstrated that seven variables were associated with cancer-specific survival (CSS) (all p < 0.05). The DeepSurv model showed better performance than the Cox-PH model (C-index: 0.871 vs. 0.866). The calibration curves and DCA revealed that the two models had good discrimination and calibration. Moreover, patients with ileac malignancy and N2 stage disease were not responding to surgery according to the K−M analysis. Conclusions This study reported a DeepSurv model that performed well in CSS in SBT patients. It might offer insights into future research to explore more DL algorithms in cohort studies." @default.
• W4280630103 created "2022-05-22" @default.
• W4280630103 creator A5003258773 @default.
• W4280630103 creator A5023358608 @default.
• W4280630103 creator A5025043316 @default.
• W4280630103 creator A5029988344 @default.
• W4280630103 creator A5049264813 @default.
• W4280630103 creator A5050789305 @default.
• W4280630103 creator A5074176076 @default.
• W4280630103 creator A5074588436 @default.
• W4280630103 creator A5079551837 @default.
• W4280630103 creator A5084408238 @default.
• W4280630103 creator A5087065513 @default.
• W4280630103 date "2022-05-17" @default.
• W4280630103 modified "2023-10-17" @default.
• W4280630103 title "Development of a Deep Learning Model for Malignant Small Bowel Tumors Survival: A SEER-Based Study" @default.
• W4280630103 cites W2077050281 @default.
• W4280630103 cites W2159543786 @default.
• W4280630103 cites W2753919178 @default.
• W4280630103 cites W2783201053 @default.
• W4280630103 cites W2785825652 @default.
• W4280630103 cites W2892679192 @default.
• W4280630103 cites W2903150666 @default.
• W4280630103 cites W2923841820 @default.
• W4280630103 cites W2948930564 @default.
• W4280630103 cites W2971594300 @default.
• W4280630103 cites W2999134910 @default.
• W4280630103 cites W3004053956 @default.
• W4280630103 cites W3017170546 @default.
• W4280630103 cites W3030808065 @default.
• W4280630103 cites W3031635948 @default.
• W4280630103 cites W3040242077 @default.
• W4280630103 cites W3047225819 @default.
• W4280630103 cites W3049537026 @default.
• W4280630103 cites W3081330175 @default.
• W4280630103 cites W3095667134 @default.
• W4280630103 cites W3100128679 @default.
• W4280630103 cites W3122193676 @default.
• W4280630103 cites W3166025287 @default.
• W4280630103 cites W3167514989 @default.
• W4280630103 cites W3170980484 @default.
• W4280630103 cites W3180696751 @default.
• W4280630103 cites W3209122246 @default.
• W4280630103 cites W3214401235 @default.
• W4280630103 cites W3215408688 @default.
• W4280630103 cites W4200286073 @default.
• W4280630103 cites W4225611710 @default.
• W4280630103 doi "https://doi.org/10.3390/diagnostics12051247" @default.
• W4280630103 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35626403" @default.
• W4280630103 hasPublicationYear "2022" @default.
• W4280630103 type Work @default.
• W4280630103 citedByCount "4" @default.
• W4280630103 countsByYear W42806301032023 @default.
• W4280630103 crossrefType "journal-article" @default.
• W4280630103 hasAuthorship W4280630103A5003258773 @default.
• W4280630103 hasAuthorship W4280630103A5023358608 @default.
• W4280630103 hasAuthorship W4280630103A5025043316 @default.
• W4280630103 hasAuthorship W4280630103A5029988344 @default.
• W4280630103 hasAuthorship W4280630103A5049264813 @default.
• W4280630103 hasAuthorship W4280630103A5050789305 @default.
• W4280630103 hasAuthorship W4280630103A5074176076 @default.
• W4280630103 hasAuthorship W4280630103A5074588436 @default.
• W4280630103 hasAuthorship W4280630103A5079551837 @default.
• W4280630103 hasAuthorship W4280630103A5084408238 @default.
• W4280630103 hasAuthorship W4280630103A5087065513 @default.
• W4280630103 hasBestOaLocation W42806301031 @default.
• W4280630103 hasConcept C10515644 @default.
• W4280630103 hasConcept C105795698 @default.
• W4280630103 hasConcept C126322002 @default.
• W4280630103 hasConcept C143998085 @default.
• W4280630103 hasConcept C146357865 @default.
• W4280630103 hasConcept C151730666 @default.
• W4280630103 hasConcept C154945302 @default.
• W4280630103 hasConcept C161584116 @default.
• W4280630103 hasConcept C165838908 @default.
• W4280630103 hasConcept C2779399171 @default.
• W4280630103 hasConcept C33923547 @default.
• W4280630103 hasConcept C38180746 @default.
• W4280630103 hasConcept C41008148 @default.
• W4280630103 hasConcept C50382708 @default.
• W4280630103 hasConcept C58471807 @default.
• W4280630103 hasConcept C71924100 @default.
• W4280630103 hasConcept C86803240 @default.
• W4280630103 hasConceptScore W4280630103C10515644 @default.
• W4280630103 hasConceptScore W4280630103C105795698 @default.
• W4280630103 hasConceptScore W4280630103C126322002 @default.
• W4280630103 hasConceptScore W4280630103C143998085 @default.
• W4280630103 hasConceptScore W4280630103C146357865 @default.
• W4280630103 hasConceptScore W4280630103C151730666 @default.
• W4280630103 hasConceptScore W4280630103C154945302 @default.
• W4280630103 hasConceptScore W4280630103C161584116 @default.
• W4280630103 hasConceptScore W4280630103C165838908 @default.
• W4280630103 hasConceptScore W4280630103C2779399171 @default.
• W4280630103 hasConceptScore W4280630103C33923547 @default.
• W4280630103 hasConceptScore W4280630103C38180746 @default.
• W4280630103 hasConceptScore W4280630103C41008148 @default.
• W4280630103 hasConceptScore W4280630103C50382708 @default.
• W4280630103 hasConceptScore W4280630103C58471807 @default.

• next