FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3083067908> ?p ?o ?g. }

• W3083067908 endingPage "105738" @default.
• W3083067908 startingPage "105738" @default.
• W3083067908 abstract "Attention-Deficit/Hyperactivity Disorder (ADHD) is a chronic behavioral disorder in children. Children with ADHD face many difficulties in maintaining their concentration and controlling their behaviors. Early diagnosis of this disorder is one of the most important challenges in its control and treatment. No definitive expert method has been found to detect this disorder early. Our goal in this study is to develop an assistive tool for physicians to recognize ADHD children from healthy children using electroencephalography (EEG) based on a continuous mental task. We used EEG signals recorded from 31 ADHD children and 30 healthy children. In this study, we developed a deep learning model using a convolutional neural network that have had significant performance in image processing fields. For this purpose, we first preprocessed EEG signals to eliminate noise and artifacts. Then we segmented preprocessed samples into more samples. We extracted the theta, alpha, beta, and gamma frequency bands from each segmented sample and formed a color RGB image with three channels. Eventually, we imported the resulting images into a 13-layer convolutional neural network for feature extraction and classification. The proposed model was evaluated by 5-fold cross validation for train, evaluation, and test data and achieved an average accuracy of 99.06%, 97.81%, 97.47% for segmented samples. The average accuracy for subject-based test samples was 98.48%. Also, the performance of the model was evaluated using the confusion matrix with precision, recall, and f1-score metrics. The results of these metrics also confirmed the outstanding performance of the model. The accuracy, precision, recall, and f1-score of our model were better than all previous works for diagnosing ADHD in children. Based on these prominent and reliable results, this technique can be used as an assistive tool for the physicians in the early diagnosis of ADHD in children." @default.
• W3083067908 created "2020-09-11" @default.
• W3083067908 creator A5012671504 @default.
• W3083067908 creator A5063416360 @default.
• W3083067908 creator A5075323116 @default.
• W3083067908 date "2020-12-01" @default.
• W3083067908 modified "2023-10-17" @default.
• W3083067908 title "Diagnose ADHD disorder in children using convolutional neural network based on continuous mental task EEG" @default.
• W3083067908 cites W1979594497 @default.
• W3083067908 cites W1996233863 @default.
• W3083067908 cites W2036206130 @default.
• W3083067908 cites W2092444833 @default.
• W3083067908 cites W2097326903 @default.
• W3083067908 cites W2120093887 @default.
• W3083067908 cites W2222496538 @default.
• W3083067908 cites W2263602591 @default.
• W3083067908 cites W2293858113 @default.
• W3083067908 cites W2295786995 @default.
• W3083067908 cites W2305715566 @default.
• W3083067908 cites W2377697875 @default.
• W3083067908 cites W2420049378 @default.
• W3083067908 cites W2512706775 @default.
• W3083067908 cites W2586011699 @default.
• W3083067908 cites W2762517398 @default.
• W3083067908 cites W2768576993 @default.
• W3083067908 cites W2797694788 @default.
• W3083067908 cites W2802815532 @default.
• W3083067908 cites W2805710794 @default.
• W3083067908 cites W2924051171 @default.
• W3083067908 cites W2938361789 @default.
• W3083067908 cites W2944352397 @default.
• W3083067908 cites W2946763314 @default.
• W3083067908 cites W2950322502 @default.
• W3083067908 cites W2963261317 @default.
• W3083067908 cites W2967781381 @default.
• W3083067908 cites W2968645924 @default.
• W3083067908 cites W2968778218 @default.
• W3083067908 cites W2972612047 @default.
• W3083067908 cites W2979102790 @default.
• W3083067908 cites W2990234362 @default.
• W3083067908 cites W2993006640 @default.
• W3083067908 cites W4236173595 @default.
• W3083067908 cites W812004106 @default.
• W3083067908 doi "https://doi.org/10.1016/j.cmpb.2020.105738" @default.
• W3083067908 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32927404" @default.
• W3083067908 hasPublicationYear "2020" @default.
• W3083067908 type Work @default.
• W3083067908 sameAs 3083067908 @default.
• W3083067908 citedByCount "47" @default.
• W3083067908 countsByYear W30830679082021 @default.
• W3083067908 countsByYear W30830679082022 @default.
• W3083067908 countsByYear W30830679082023 @default.
• W3083067908 crossrefType "journal-article" @default.
• W3083067908 hasAuthorship W3083067908A5012671504 @default.
• W3083067908 hasAuthorship W3083067908A5063416360 @default.
• W3083067908 hasAuthorship W3083067908A5075323116 @default.
• W3083067908 hasConcept C108583219 @default.
• W3083067908 hasConcept C118552586 @default.
• W3083067908 hasConcept C138602881 @default.
• W3083067908 hasConcept C138885662 @default.
• W3083067908 hasConcept C153180895 @default.
• W3083067908 hasConcept C154945302 @default.
• W3083067908 hasConcept C15744967 @default.
• W3083067908 hasConcept C162324750 @default.
• W3083067908 hasConcept C187736073 @default.
• W3083067908 hasConcept C2776401178 @default.
• W3083067908 hasConcept C2780451532 @default.
• W3083067908 hasConcept C2780783007 @default.
• W3083067908 hasConcept C41008148 @default.
• W3083067908 hasConcept C41895202 @default.
• W3083067908 hasConcept C50644808 @default.
• W3083067908 hasConcept C522805319 @default.
• W3083067908 hasConcept C52622490 @default.
• W3083067908 hasConcept C548259974 @default.
• W3083067908 hasConcept C71924100 @default.
• W3083067908 hasConcept C81363708 @default.
• W3083067908 hasConceptScore W3083067908C108583219 @default.
• W3083067908 hasConceptScore W3083067908C118552586 @default.
• W3083067908 hasConceptScore W3083067908C138602881 @default.
• W3083067908 hasConceptScore W3083067908C138885662 @default.
• W3083067908 hasConceptScore W3083067908C153180895 @default.
• W3083067908 hasConceptScore W3083067908C154945302 @default.
• W3083067908 hasConceptScore W3083067908C15744967 @default.
• W3083067908 hasConceptScore W3083067908C162324750 @default.
• W3083067908 hasConceptScore W3083067908C187736073 @default.
• W3083067908 hasConceptScore W3083067908C2776401178 @default.
• W3083067908 hasConceptScore W3083067908C2780451532 @default.
• W3083067908 hasConceptScore W3083067908C2780783007 @default.
• W3083067908 hasConceptScore W3083067908C41008148 @default.
• W3083067908 hasConceptScore W3083067908C41895202 @default.
• W3083067908 hasConceptScore W3083067908C50644808 @default.
• W3083067908 hasConceptScore W3083067908C522805319 @default.
• W3083067908 hasConceptScore W3083067908C52622490 @default.
• W3083067908 hasConceptScore W3083067908C548259974 @default.
• W3083067908 hasConceptScore W3083067908C71924100 @default.
• W3083067908 hasConceptScore W3083067908C81363708 @default.
• W3083067908 hasLocation W30830679081 @default.
• W3083067908 hasOpenAccess W3083067908 @default.

• next