186 related articles for article (PubMed ID: 34411269)
1. Classification of Autism Spectrum Disorder From EEG-Based Functional Brain Connectivity Analysis.
Alotaibi N; Maharatna K
Neural Comput; 2021 Jun; 33(7):1914-1941. PubMed ID: 34411269
[TBL] [Abstract][Full Text] [Related]
2. Functional connectivity based machine learning approach for autism detection in young children using MEG signals.
Barik K; Watanabe K; Bhattacharya J; Saha G
J Neural Eng; 2023 Mar; 20(2):. PubMed ID: 36812588
[No Abstract] [Full Text] [Related]
3. Diagnosis of Autism Spectrum Disorder by Dynamic Local Graph-Theory Indicators Based on Electroencephalogram.
Luo H; Yang S; Zhang N; Huang L; Ge Y; Chen A; Zhu J; Zhang J
J Integr Neurosci; 2024 May; 23(5):95. PubMed ID: 38812386
[TBL] [Abstract][Full Text] [Related]
4. Multivariate classification of autism spectrum disorder using frequency-specific resting-state functional connectivity--A multi-center study.
Chen H; Duan X; Liu F; Lu F; Ma X; Zhang Y; Uddin LQ; Chen H
Prog Neuropsychopharmacol Biol Psychiatry; 2016 Jan; 64():1-9. PubMed ID: 26148789
[TBL] [Abstract][Full Text] [Related]
5. State-Dependent Differences in Functional Connectivity in Young Children With Autism Spectrum Disorder.
Buckley AW; Scott R; Tyler A; Mahoney JM; Thurm A; Farmer C; Swedo S; Burroughs SA; Holmes GL
EBioMedicine; 2015 Dec; 2(12):1905-15. PubMed ID: 26844269
[TBL] [Abstract][Full Text] [Related]
6. The "MS-ROM/IFAST" Model, a Novel Parallel Nonlinear EEG Analysis Technique, Distinguishes ASD Subjects From Children Affected With Other Neuropsychiatric Disorders With High Degree of Accuracy.
Grossi E; Buscema M; Della Torre F; Swatzyna RJ
Clin EEG Neurosci; 2019 Sep; 50(5):319-331. PubMed ID: 31296052
[No Abstract] [Full Text] [Related]
7. Conditional entropy approach to analyze cognitive dynamics in autism spectrum disorder.
Wadhera T; Kakkar D
Neurol Res; 2020 Oct; 42(10):869-878. PubMed ID: 32628095
[TBL] [Abstract][Full Text] [Related]
8. Band-specific atypical functional connectivity pattern in childhood autism spectrum disorder.
Takahashi T; Yamanishi T; Nobukawa S; Kasakawa S; Yoshimura Y; Hiraishi H; Hasegawa C; Ikeda T; Hirosawa T; Munesue T; Higashida H; Minabe Y; Kikuchi M
Clin Neurophysiol; 2017 Aug; 128(8):1457-1465. PubMed ID: 28622528
[TBL] [Abstract][Full Text] [Related]
9. Aberrant functional connectivity of neural circuits associated with social and sensorimotor deficits in young children with autism spectrum disorder.
Chen H; Wang J; Uddin LQ; Wang X; Guo X; Lu F; Duan X; Wu L; Chen H
Autism Res; 2018 Dec; 11(12):1643-1652. PubMed ID: 30475453
[TBL] [Abstract][Full Text] [Related]
10. Enhancing autism spectrum disorder classification in children through the integration of traditional statistics and classical machine learning techniques in EEG analysis.
Rogala J; Żygierewicz J; Malinowska U; Cygan H; Stawicka E; Kobus A; Vanrumste B
Sci Rep; 2023 Dec; 13(1):21748. PubMed ID: 38066046
[TBL] [Abstract][Full Text] [Related]
11. Multivariate Neural Connectivity Patterns in Early Infancy Predict Later Autism Symptoms.
Dickinson A; Daniel M; Marin A; Gaonkar B; Dapretto M; McDonald NM; Jeste S
Biol Psychiatry Cogn Neurosci Neuroimaging; 2021 Jan; 6(1):59-69. PubMed ID: 32798139
[TBL] [Abstract][Full Text] [Related]
12. Identification of autism spectrum disorder based on electroencephalography: A systematic review.
Li J; Kong X; Sun L; Chen X; Ouyang G; Li X; Chen S
Comput Biol Med; 2024 Mar; 170():108075. PubMed ID: 38301514
[TBL] [Abstract][Full Text] [Related]
13. A spectrogram image based intelligent technique for automatic detection of autism spectrum disorder from EEG.
Tawhid MNA; Siuly S; Wang H; Whittaker F; Wang K; Zhang Y
PLoS One; 2021; 16(6):e0253094. PubMed ID: 34170979
[TBL] [Abstract][Full Text] [Related]
14. Stimulus dependent neural oscillatory patterns show reliable statistical identification of autism spectrum disorder in a face perceptual decision task.
Castelhano J; Tavares P; Mouga S; Oliveira G; Castelo-Branco M
Clin Neurophysiol; 2018 May; 129(5):981-989. PubMed ID: 29554581
[TBL] [Abstract][Full Text] [Related]
15. Linear and nonlinear analysis of intrinsic mode function after facial stimuli presentation in children with autism spectrum disorder.
Bakheet D; Maharatna K
Comput Biol Med; 2021 Jun; 133():104376. PubMed ID: 33866255
[TBL] [Abstract][Full Text] [Related]
16. [Electroencephalogram feature extraction and classification of autistic children based on recurrence quantification analysis].
Zhao J; Zhang Z; Wan L; Li X; Kang J
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2021 Aug; 38(4):663-670. PubMed ID: 34459165
[TBL] [Abstract][Full Text] [Related]
17. Automatic classification of autism spectrum disorder in children using cortical thickness and support vector machine.
Squarcina L; Nosari G; Marin R; Castellani U; Bellani M; Bonivento C; Fabbro F; Molteni M; Brambilla P
Brain Behav; 2021 Aug; 11(8):e2238. PubMed ID: 34264004
[TBL] [Abstract][Full Text] [Related]
18. Changes in Electroencephalogram Coherence in Adolescents With Autism Spectrum Disorder After a Social Skills Intervention.
Haendel AD; Barrington A; Magnus B; Arias AA; McVey A; Pleiss S; Carson A; Vogt EM; Van Hecke AV
Autism Res; 2021 Apr; 14(4):787-803. PubMed ID: 33398936
[TBL] [Abstract][Full Text] [Related]
19. The identification of children with autism spectrum disorder by SVM approach on EEG and eye-tracking data.
Kang J; Han X; Song J; Niu Z; Li X
Comput Biol Med; 2020 May; 120():103722. PubMed ID: 32250854
[TBL] [Abstract][Full Text] [Related]
20. Application of Machine Learning Techniques to Detect the Children with Autism Spectrum Disorder.
Liao M; Duan H; Wang G
J Healthc Eng; 2022; 2022():9340027. PubMed ID: 35368925
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
