FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4289277935> ?p ?o ?g. }

• W4289277935 abstract "Diffusion-weighted (DW) imaging is a well-recognized magnetic resonance imaging (MRI) technique that is being routinely used in brain examinations in modern clinical radiology practices. This study focuses on extracting demographic and texture features from MRI Apparent Diffusion Coefficient (ADC) images of human brain tumors, identifying the distribution patterns of each feature and applying Machine Learning (ML) techniques to differentiate malignant from benign brain tumors.This prospective study was carried out using 1599 labeled MRI brain ADC image slices, 995 malignant, 604 benign from 195 patients who were radiologically diagnosed and histopathologically confirmed as brain tumor patients. The demographics, mean pixel values, skewness, kurtosis, features of Grey Level Co-occurrence Matrix (GLCM), mean, variance, energy, entropy, contrast, homogeneity, correlation, prominence and shade, were extracted from MRI ADC images of each patient. At the feature selection phase, the validity of the extracted features were measured using ANOVA f-test. Then, these features were used as input to several Machine Learning classification algorithms and the respective models were assessed.According to the results of ANOVA f-test feature selection process, two attributes: skewness (3.34) and GLCM homogeneity (3.45) scored the lowest ANOVA f-test scores. Therefore, both features were excluded in continuation of the experiment. From the different tested ML algorithms, the Random Forest classifier was chosen to build the final ML model, since it presented the highest accuracy. The final model was able to predict malignant and benign neoplasms with an 90.41% accuracy after the hyper parameter tuning process.This study concludes that the above mentioned features (except skewness and GLCM homogeneity) are informative to identify and differentiate malignant from benign brain tumors. Moreover, they enable the development of a high-performance ML model that has the ability to assist in the decision-making steps of brain tumor diagnosis process, prior to attempting invasive diagnostic procedures, such as brain biopsies." @default.
• W4289277935 created "2022-08-01" @default.
• W4289277935 creator A5012655790 @default.
• W4289277935 creator A5040863927 @default.
• W4289277935 creator A5050474434 @default.
• W4289277935 creator A5055515696 @default.
• W4289277935 creator A5055856596 @default.
• W4289277935 creator A5058198811 @default.
• W4289277935 creator A5077172377 @default.
• W4289277935 creator A5085523573 @default.
• W4289277935 creator A5089712816 @default.
• W4289277935 date "2022-08-01" @default.
• W4289277935 modified "2023-10-03" @default.
• W4289277935 title "Feature extraction from MRI ADC images for brain tumor classification using machine learning techniques" @default.
• W4289277935 cites W1580128294 @default.
• W4289277935 cites W1897881764 @default.
• W4289277935 cites W1963703920 @default.
• W4289277935 cites W1966705856 @default.
• W4289277935 cites W1972366663 @default.
• W4289277935 cites W1977618291 @default.
• W4289277935 cites W1994961181 @default.
• W4289277935 cites W1998865404 @default.
• W4289277935 cites W2003775260 @default.
• W4289277935 cites W2031071736 @default.
• W4289277935 cites W2031534613 @default.
• W4289277935 cites W2032309439 @default.
• W4289277935 cites W2033160702 @default.
• W4289277935 cites W2048874541 @default.
• W4289277935 cites W2075851722 @default.
• W4289277935 cites W2082738326 @default.
• W4289277935 cites W2088553141 @default.
• W4289277935 cites W2090575716 @default.
• W4289277935 cites W2096526848 @default.
• W4289277935 cites W2100803151 @default.
• W4289277935 cites W2116531017 @default.
• W4289277935 cites W2122343711 @default.
• W4289277935 cites W2125687380 @default.
• W4289277935 cites W2145423090 @default.
• W4289277935 cites W2148977460 @default.
• W4289277935 cites W2334742858 @default.
• W4289277935 cites W2524124781 @default.
• W4289277935 cites W2568424517 @default.
• W4289277935 cites W2807039030 @default.
• W4289277935 cites W2947374264 @default.
• W4289277935 cites W2957754238 @default.
• W4289277935 cites W2971147046 @default.
• W4289277935 cites W4234865248 @default.
• W4289277935 cites W4245160364 @default.
• W4289277935 doi "https://doi.org/10.1186/s12938-022-01022-6" @default.
• W4289277935 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35915448" @default.
• W4289277935 hasPublicationYear "2022" @default.
• W4289277935 type Work @default.
• W4289277935 citedByCount "5" @default.
• W4289277935 countsByYear W42892779352022 @default.
• W4289277935 countsByYear W42892779352023 @default.
• W4289277935 crossrefType "journal-article" @default.
• W4289277935 hasAuthorship W4289277935A5012655790 @default.
• W4289277935 hasAuthorship W4289277935A5040863927 @default.
• W4289277935 hasAuthorship W4289277935A5050474434 @default.
• W4289277935 hasAuthorship W4289277935A5055515696 @default.
• W4289277935 hasAuthorship W4289277935A5055856596 @default.
• W4289277935 hasAuthorship W4289277935A5058198811 @default.
• W4289277935 hasAuthorship W4289277935A5077172377 @default.
• W4289277935 hasAuthorship W4289277935A5085523573 @default.
• W4289277935 hasAuthorship W4289277935A5089712816 @default.
• W4289277935 hasBestOaLocation W42892779351 @default.
• W4289277935 hasConcept C105795698 @default.
• W4289277935 hasConcept C122342681 @default.
• W4289277935 hasConcept C126838900 @default.
• W4289277935 hasConcept C142724271 @default.
• W4289277935 hasConcept C143409427 @default.
• W4289277935 hasConcept C148483581 @default.
• W4289277935 hasConcept C149550507 @default.
• W4289277935 hasConcept C153180895 @default.
• W4289277935 hasConcept C154945302 @default.
• W4289277935 hasConcept C166963901 @default.
• W4289277935 hasConcept C169258074 @default.
• W4289277935 hasConcept C2779130545 @default.
• W4289277935 hasConcept C2989005 @default.
• W4289277935 hasConcept C33923547 @default.
• W4289277935 hasConcept C41008148 @default.
• W4289277935 hasConcept C52622490 @default.
• W4289277935 hasConcept C70816921 @default.
• W4289277935 hasConcept C71924100 @default.
• W4289277935 hasConceptScore W4289277935C105795698 @default.
• W4289277935 hasConceptScore W4289277935C122342681 @default.
• W4289277935 hasConceptScore W4289277935C126838900 @default.
• W4289277935 hasConceptScore W4289277935C142724271 @default.
• W4289277935 hasConceptScore W4289277935C143409427 @default.
• W4289277935 hasConceptScore W4289277935C148483581 @default.
• W4289277935 hasConceptScore W4289277935C149550507 @default.
• W4289277935 hasConceptScore W4289277935C153180895 @default.
• W4289277935 hasConceptScore W4289277935C154945302 @default.
• W4289277935 hasConceptScore W4289277935C166963901 @default.
• W4289277935 hasConceptScore W4289277935C169258074 @default.
• W4289277935 hasConceptScore W4289277935C2779130545 @default.
• W4289277935 hasConceptScore W4289277935C2989005 @default.
• W4289277935 hasConceptScore W4289277935C33923547 @default.
• W4289277935 hasConceptScore W4289277935C41008148 @default.
• W4289277935 hasConceptScore W4289277935C52622490 @default.

• next