134 related articles for article (PubMed ID: 38457850)
1. Identifying autism using EEG: unleashing the power of feature selection and machine learning.
Ranaut A; Khandnor P; Chand T
Biomed Phys Eng Express; 2024 Mar; 10(3):. PubMed ID: 38457850
[TBL] [Abstract][Full Text] [Related]
2. Prediction of autism spectrum disorder diagnosis using nonlinear measures of language-related EEG at 6 and 12 months.
Peck FC; Gabard-Durnam LJ; Wilkinson CL; Bosl W; Tager-Flusberg H; Nelson CA
J Neurodev Disord; 2021 Nov; 13(1):57. PubMed ID: 34847887
[TBL] [Abstract][Full Text] [Related]
3. Detection of an Autism EEG Signature From Only Two EEG Channels Through Features Extraction and Advanced Machine Learning Analysis.
Grossi E; Valbusa G; Buscema M
Clin EEG Neurosci; 2021 Sep; 52(5):330-337. PubMed ID: 33349054
[TBL] [Abstract][Full Text] [Related]
4. Mobile detection of autism through machine learning on home video: A development and prospective validation study.
Tariq Q; Daniels J; Schwartz JN; Washington P; Kalantarian H; Wall DP
PLoS Med; 2018 Nov; 15(11):e1002705. PubMed ID: 30481180
[TBL] [Abstract][Full Text] [Related]
5. EEG-based multi-feature fusion assessment for autism.
Kang J; Zhou T; Han J; Li X
J Clin Neurosci; 2018 Oct; 56():101-107. PubMed ID: 30318070
[TBL] [Abstract][Full Text] [Related]
6. Accurate assessment of low-function autistic children based on EEG feature fusion.
Kang J; Jin Y; Liang G; Li X
J Clin Neurosci; 2021 Aug; 90():351-358. PubMed ID: 34275574
[TBL] [Abstract][Full Text] [Related]
7. Diagnosis of autism through EEG processed by advanced computational algorithms: A pilot study.
Grossi E; Olivieri C; Buscema M
Comput Methods Programs Biomed; 2017 Apr; 142():73-79. PubMed ID: 28325448
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. 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]
10. The study of the differences between low-functioning autistic children and typically developing children in the processing of the own-race and other-race faces by the machine learning approach.
Kang J; Han X; Hu JF; Feng H; Li X
J Clin Neurosci; 2020 Nov; 81():54-60. PubMed ID: 33222968
[TBL] [Abstract][Full Text] [Related]
11. A new classification system for autism based on machine learning of artificial intelligence.
Shahamiri SR; Thabtah F; Abdelhamid N
Technol Health Care; 2022; 30(3):605-622. PubMed ID: 34657857
[TBL] [Abstract][Full Text] [Related]
12. Automated ASD detection using hybrid deep lightweight features extracted from EEG signals.
Baygin M; Dogan S; Tuncer T; Datta Barua P; Faust O; Arunkumar N; Abdulhay EW; Emma Palmer E; Rajendra Acharya U
Comput Biol Med; 2021 Jul; 134():104548. PubMed ID: 34119923
[TBL] [Abstract][Full Text] [Related]
13. Computer-aided diagnosis of autism spectrum disorder from EEG signals using deep learning with FAWT and multiscale permutation entropy features.
Chawla P; Rana SB; Kaur H; Singh K
Proc Inst Mech Eng H; 2023 Feb; 237(2):282-294. PubMed ID: 36515392
[TBL] [Abstract][Full Text] [Related]
14. Identification of newborns at risk for autism using electronic medical records and machine learning.
Rahman R; Kodesh A; Levine SZ; Sandin S; Reichenberg A; Schlessinger A
Eur Psychiatry; 2020 Feb; 63(1):e22. PubMed ID: 32100657
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. Identification of atypical sleep microarchitecture biomarkers in children with autism spectrum disorder.
Martinez C; Chen ZS
Front Psychiatry; 2023; 14():1115374. PubMed ID: 37139324
[TBL] [Abstract][Full Text] [Related]
17. An Improved AlexNet Model and Cepstral Coefficient-Based Classification of Autism Using EEG.
Menaka R; Karthik R; Saranya S; Niranjan M; Kabilan S
Clin EEG Neurosci; 2024 Jan; 55(1):43-51. PubMed ID: 37246419
[TBL] [Abstract][Full Text] [Related]
18. Resting state EEG power spectrum and functional connectivity in autism: a cross-sectional analysis.
Garcés P; Baumeister S; Mason L; Chatham CH; Holiga S; Dukart J; Jones EJH; Banaschewski T; Baron-Cohen S; Bölte S; Buitelaar JK; Durston S; Oranje B; Persico AM; Beckmann CF; Bougeron T; Dell'Acqua F; Ecker C; Moessnang C; Charman T; Tillmann J; Murphy DGM; Johnson M; Loth E; Brandeis D; Hipp JF;
Mol Autism; 2022 May; 13(1):22. PubMed ID: 35585637
[TBL] [Abstract][Full Text] [Related]
19. Detecting Developmental Delay and Autism Through Machine Learning Models Using Home Videos of Bangladeshi Children: Development and Validation Study.
Tariq Q; Fleming SL; Schwartz JN; Dunlap K; Corbin C; Washington P; Kalantarian H; Khan NZ; Darmstadt GL; Wall DP
J Med Internet Res; 2019 Apr; 21(4):e13822. PubMed ID: 31017583
[TBL] [Abstract][Full Text] [Related]
20. Machine learning in autistic spectrum disorder behavioral research: A review and ways forward.
Thabtah F
Inform Health Soc Care; 2019 Sep; 44(3):278-297. PubMed ID: 29436887
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
