These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
149 related articles for article (PubMed ID: 38332856)
41. 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]
42. 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]
43. Divergent electroencephalogram resting-state functional network alterations in subgroups of autism spectrum disorder: a symptom-based clustering analysis. Zhu G; Li Y; Wan L; Sun C; Liu X; Zhang J; Liang Y; Liu G; Yan H; Li R; Yang G Cereb Cortex; 2024 Jan; 34(1):. PubMed ID: 37950877 [TBL] [Abstract][Full Text] [Related]
44. Electroencephalogram coherence in children with and without autism spectrum disorders: decreased interhemispheric connectivity in autism. Carson AM; Salowitz NM; Scheidt RA; Dolan BK; Van Hecke AV Autism Res; 2014 Jun; 7(3):334-43. PubMed ID: 24623657 [TBL] [Abstract][Full Text] [Related]
45. Identification of Autism Subtypes Based on Wavelet Coherence of BOLD FMRI Signals Using Convolutional Neural Network. Al-Hiyali MI; Yahya N; Faye I; Hussein AF Sensors (Basel); 2021 Aug; 21(16):. PubMed ID: 34450699 [TBL] [Abstract][Full Text] [Related]
46. Resting-state EEG patterns of preschool-aged boys with autism spectrum disorder: A pilot study. Zhao Q; Luo Y; Mei X; Shao Z Appl Neuropsychol Child; 2024; 13(4):413-420. PubMed ID: 37172019 [TBL] [Abstract][Full Text] [Related]
47. Identifying Boys With Autism Spectrum Disorder Based on Whole-Brain Resting-State Interregional Functional Connections Using a Boruta-Based Support Vector Machine Approach. Zhao L; Sun YK; Xue SW; Luo H; Lu XD; Zhang LH Front Neuroinform; 2022; 16():761942. PubMed ID: 35273487 [TBL] [Abstract][Full Text] [Related]
48. A Review of Machine Learning Methods of Feature Selection and Classification for Autism Spectrum Disorder. Rahman MM; Usman OL; Muniyandi RC; Sahran S; Mohamed S; Razak RA Brain Sci; 2020 Dec; 10(12):. PubMed ID: 33297436 [TBL] [Abstract][Full Text] [Related]
49. Baseline EEG in the first year of life: Preliminary insights into the development of autism spectrum disorder and language impairments. Piazza C; Dondena C; Riboldi EM; Riva V; Cantiani C iScience; 2023 Jul; 26(7):106987. PubMed ID: 37534149 [TBL] [Abstract][Full Text] [Related]
50. Speech Reception in Young Children with Autism Is Selectively Indexed by a Neural Oscillation Coupling Anomaly. Wang X; Delgado J; Marchesotti S; Kojovic N; Sperdin HF; Rihs TA; Schaer M; Giraud AL J Neurosci; 2023 Oct; 43(40):6779-6795. PubMed ID: 37607822 [TBL] [Abstract][Full Text] [Related]
51. Robust features for the automatic identification of autism spectrum disorder in children. Eldridge J; Lane AE; Belkin M; Dennis S J Neurodev Disord; 2014; 6(1):12. PubMed ID: 24936212 [TBL] [Abstract][Full Text] [Related]
52. 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]
53. 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]
54. 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]
55. Brain functional networks in syndromic and non-syndromic autism: a graph theoretical study of EEG connectivity. Peters JM; Taquet M; Vega C; Jeste SS; Fernández IS; Tan J; Nelson CA; Sahin M; Warfield SK BMC Med; 2013 Feb; 11():54. PubMed ID: 23445896 [TBL] [Abstract][Full Text] [Related]
56. Reduced frontal gamma power at 24 months is associated with better expressive language in toddlers at risk for autism. Wilkinson CL; Levin AR; Gabard-Durnam LJ; Tager-Flusberg H; Nelson CA Autism Res; 2019 Aug; 12(8):1211-1224. PubMed ID: 31119899 [TBL] [Abstract][Full Text] [Related]
57. Resting state cortical connectivity reflected in EEG coherence in individuals with autism. Murias M; Webb SJ; Greenson J; Dawson G Biol Psychiatry; 2007 Aug; 62(3):270-3. PubMed ID: 17336944 [TBL] [Abstract][Full Text] [Related]
58. Cortico-Cerebellar neurodynamics during social interaction in Autism Spectrum Disorders. Gaudfernau F; Lefebvre A; Engemann DA; Pedoux A; Bánki A; Baillin F; Landman B; Maruani A; Amsellem F; Bourgeron T; Delorme R; Dumas G Neuroimage Clin; 2023; 39():103465. PubMed ID: 37454469 [TBL] [Abstract][Full Text] [Related]
59. fMRI-Based Multi-class DMDC Model Efficiently Decodes the Overlaps between ASD and ADHD. Zolghadr Z; Batouli SAH; Alavi Majd H; Shafaghi L; Mehrabi Y Basic Clin Neurosci; 2024; 15(3):367-382. PubMed ID: 39403359 [TBL] [Abstract][Full Text] [Related]
60. Resting state EEG in youth with ASD: age, sex, and relation to phenotype. Neuhaus E; Lowry SJ; Santhosh M; Kresse A; Edwards LA; Keller J; Libsack EJ; Kang VY; Naples A; Jack A; Jeste S; McPartland JC; Aylward E; Bernier R; Bookheimer S; Dapretto M; Van Horn JD; Pelphrey K; Webb SJ; J Neurodev Disord; 2021 Sep; 13(1):33. PubMed ID: 34517813 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]