FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4376111519> ?p ?o ?g. }

• W4376111519 endingPage "105006" @default.
• W4376111519 startingPage "105006" @default.
• W4376111519 abstract "The brain is a complex organ and Magnetic Resonance Imaging (MRI) is the most widely used imaging modality for diagnosing brain diseases due to its superior soft tissue contrast. In clinical practice, interpreting MRI scans is laborious, time-consuming, and error-prone. While most studies focus on detecting brain tumors and multiple sclerosis, there are limited studies on atrophy, ischemia, and white matter intensity (WMI) diseases. Moreover, most studies are complex, time-consuming, computationally intensive, and specific to the detection of a particular brain disease. Our study presents a new deep learning-based ensemble model and also introduces the novel double iterative ReliefF (DIRF) feature selection algorithm to enhance the performance of automatic detection of atrophy, ischemia, and WMI using MRI images. Two pre-trained deep models, namely AlexNet and GoogleNet, and three well-known local texture descriptors, namely pyramid histogram of oriented gradients (PHOG), binary Gabor pattern (BGP), and binarized statistical image features (BSIF), were employed as feature extractors, and the extracted features were merged. The merged features were fed into the proposed double iterative ReliefF (DIRF) feature selection algorithm, and the most important 688 features were selected. Finally, the selected features were classified by support vector machine (SVM). Our proposed DIRF-based ensemble model achieved 98.87 % accuracy using a 10-fold cross-validation strategy. Our proposed model developed using a public brain diseases MRI dataset achieved an accuracy of 95.96 %. This study demonstrates that our proposed model, with DIRF feature selection algorithm can significantly improve the diagnosis of various brain diseases, enhancing the patient care and outcomes." @default.
• W4376111519 created "2023-05-12" @default.
• W4376111519 creator A5014733456 @default.
• W4376111519 creator A5045216943 @default.
• W4376111519 creator A5045783666 @default.
• W4376111519 creator A5067380107 @default.
• W4376111519 creator A5089644161 @default.
• W4376111519 date "2023-08-01" @default.
• W4376111519 modified "2023-10-03" @default.
• W4376111519 title "Application of novel DIRF feature selection algorithm for automated brain disease detection" @default.
• W4376111519 cites W1532551225 @default.
• W4376111519 cites W1542966809 @default.
• W4376111519 cites W1607979445 @default.
• W4376111519 cites W1808644423 @default.
• W4376111519 cites W1967551258 @default.
• W4376111519 cites W2039051707 @default.
• W4376111519 cites W2097117768 @default.
• W4376111519 cites W2113855951 @default.
• W4376111519 cites W2154683974 @default.
• W4376111519 cites W2168953509 @default.
• W4376111519 cites W2170133641 @default.
• W4376111519 cites W2194775991 @default.
• W4376111519 cites W2210837254 @default.
• W4376111519 cites W2295835678 @default.
• W4376111519 cites W2762747243 @default.
• W4376111519 cites W2795896985 @default.
• W4376111519 cites W2955805844 @default.
• W4376111519 cites W2959687571 @default.
• W4376111519 cites W2963163009 @default.
• W4376111519 cites W2963446712 @default.
• W4376111519 cites W2964278775 @default.
• W4376111519 cites W2979487364 @default.
• W4376111519 cites W2994834352 @default.
• W4376111519 cites W3004866273 @default.
• W4376111519 cites W3023374095 @default.
• W4376111519 cites W3083138635 @default.
• W4376111519 cites W3089168916 @default.
• W4376111519 cites W3092504335 @default.
• W4376111519 cites W3093905802 @default.
• W4376111519 cites W3097251131 @default.
• W4376111519 cites W3120795911 @default.
• W4376111519 cites W3121092655 @default.
• W4376111519 cites W3132451580 @default.
• W4376111519 cites W3140854437 @default.
• W4376111519 cites W3156975676 @default.
• W4376111519 cites W3170968284 @default.
• W4376111519 cites W3199298121 @default.
• W4376111519 cites W3199398663 @default.
• W4376111519 cites W3201141954 @default.
• W4376111519 cites W3211147476 @default.
• W4376111519 cites W3217453598 @default.
• W4376111519 cites W4200238408 @default.
• W4376111519 cites W4206822382 @default.
• W4376111519 cites W4214663951 @default.
• W4376111519 cites W4220793704 @default.
• W4376111519 cites W4220811008 @default.
• W4376111519 cites W4220938439 @default.
• W4376111519 cites W4224053403 @default.
• W4376111519 cites W4224932948 @default.
• W4376111519 cites W4280597344 @default.
• W4376111519 cites W4280619560 @default.
• W4376111519 cites W4282941464 @default.
• W4376111519 cites W4310861931 @default.
• W4376111519 cites W4313443585 @default.
• W4376111519 cites W996251949 @default.
• W4376111519 doi "https://doi.org/10.1016/j.bspc.2023.105006" @default.
• W4376111519 hasPublicationYear "2023" @default.
• W4376111519 type Work @default.
• W4376111519 citedByCount "1" @default.
• W4376111519 crossrefType "journal-article" @default.
• W4376111519 hasAuthorship W4376111519A5014733456 @default.
• W4376111519 hasAuthorship W4376111519A5045216943 @default.
• W4376111519 hasAuthorship W4376111519A5045783666 @default.
• W4376111519 hasAuthorship W4376111519A5067380107 @default.
• W4376111519 hasAuthorship W4376111519A5089644161 @default.
• W4376111519 hasConcept C115961682 @default.
• W4376111519 hasConcept C12267149 @default.
• W4376111519 hasConcept C138885662 @default.
• W4376111519 hasConcept C142575187 @default.
• W4376111519 hasConcept C148483581 @default.
• W4376111519 hasConcept C153180895 @default.
• W4376111519 hasConcept C154945302 @default.
• W4376111519 hasConcept C17426736 @default.
• W4376111519 hasConcept C2524010 @default.
• W4376111519 hasConcept C2776401178 @default.
• W4376111519 hasConcept C33923547 @default.
• W4376111519 hasConcept C41008148 @default.
• W4376111519 hasConcept C41895202 @default.
• W4376111519 hasConcept C53533937 @default.
• W4376111519 hasConcept C81363708 @default.
• W4376111519 hasConcept C87335442 @default.
• W4376111519 hasConceptScore W4376111519C115961682 @default.
• W4376111519 hasConceptScore W4376111519C12267149 @default.
• W4376111519 hasConceptScore W4376111519C138885662 @default.
• W4376111519 hasConceptScore W4376111519C142575187 @default.
• W4376111519 hasConceptScore W4376111519C148483581 @default.
• W4376111519 hasConceptScore W4376111519C153180895 @default.
• W4376111519 hasConceptScore W4376111519C154945302 @default.

• next