361 related articles for article (PubMed ID: 25652603)
1. Use of Machine Learning to Identify Children with Autism and Their Motor Abnormalities.
Crippa A; Salvatore C; Perego P; Forti S; Nobile M; Molteni M; Castiglioni I
J Autism Dev Disord; 2015 Jul; 45(7):2146-56. PubMed ID: 25652603
[TBL] [Abstract][Full Text] [Related]
2. Identifying the signature of prospective motor control in children with autism.
Cavallo A; Romeo L; Ansuini C; Battaglia F; Nobili L; Pontil M; Panzeri S; Becchio C
Sci Rep; 2021 Feb; 11(1):3165. PubMed ID: 33542311
[TBL] [Abstract][Full Text] [Related]
3. Identifying children with autism spectrum disorder based on their face processing abnormality: A machine learning framework.
Liu W; Li M; Yi L
Autism Res; 2016 Aug; 9(8):888-98. PubMed ID: 27037971
[TBL] [Abstract][Full Text] [Related]
4. Do planning and visual integration difficulties underpin motor dysfunction in autism? A kinematic study of young children with autism.
Dowd AM; McGinley JL; Taffe JR; Rinehart NJ
J Autism Dev Disord; 2012 Aug; 42(8):1539-48. PubMed ID: 22105140
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. A Novel Approach to Enhancing Upper Extremity Coordination in Children with Autism Spectrum Disorder.
Gamez Corral AS; Manning R; Wang C; Cisneros A; Meeuwsen HJ; Boyle JB
J Mot Behav; 2020; 52(3):311-317. PubMed ID: 31232185
[TBL] [Abstract][Full Text] [Related]
7. Toward a motor signature in autism: Studies from human-machine interaction.
Xavier J; Guedjou H; Anzalone SM; Boucenna S; Guigon E; Chetouani M; Cohen D
Encephale; 2019 Apr; 45(2):182-187. PubMed ID: 30503684
[TBL] [Abstract][Full Text] [Related]
8. Three-Dimensional Kinematic Analysis of Prehension Movements in Young Children with Autism Spectrum Disorder: New Insights on Motor Impairment.
Campione GC; Piazza C; Villa L; Molteni M
J Autism Dev Disord; 2016 Jun; 46(6):1985-1999. PubMed ID: 26861718
[TBL] [Abstract][Full Text] [Related]
9. Functional but Inefficient Kinesthetic Motor Imagery in Adolescents with Autism Spectrum Disorder.
Chen YT; Tsou KS; Chen HL; Wong CC; Fan YT; Wu CT
J Autism Dev Disord; 2018 Mar; 48(3):784-795. PubMed ID: 29119522
[TBL] [Abstract][Full Text] [Related]
10. Temporal Processing Instability with Millisecond Accuracy is a Cardinal Feature of Sensorimotor Impairments in Autism Spectrum Disorder: Analysis Using the Synchronized Finger-Tapping Task.
Morimoto C; Hida E; Shima K; Okamura H
J Autism Dev Disord; 2018 Feb; 48(2):351-360. PubMed ID: 28988374
[TBL] [Abstract][Full Text] [Related]
11. Altered Gamma Oscillations during Motor Control in Children with Autism Spectrum Disorder.
An KM; Ikeda T; Yoshimura Y; Hasegawa C; Saito DN; Kumazaki H; Hirosawa T; Minabe Y; Kikuchi M
J Neurosci; 2018 Sep; 38(36):7878-7886. PubMed ID: 30104338
[TBL] [Abstract][Full Text] [Related]
12. Comparing motor performance, praxis, coordination, and interpersonal synchrony between children with and without Autism Spectrum Disorder (ASD).
Kaur M; M Srinivasan S; N Bhat A
Res Dev Disabil; 2018 Jan; 72():79-95. PubMed ID: 29121516
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Applying machine learning to identify autistic adults using imitation: An exploratory study.
Li B; Sharma A; Meng J; Purushwalkam S; Gowen E
PLoS One; 2017; 12(8):e0182652. PubMed ID: 28813454
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. Metabolomics as a tool for discovery of biomarkers of autism spectrum disorder in the blood plasma of children.
West PR; Amaral DG; Bais P; Smith AM; Egnash LA; Ross ME; Palmer JA; Fontaine BR; Conard KR; Corbett BA; Cezar GG; Donley EL; Burrier RE
PLoS One; 2014; 9(11):e112445. PubMed ID: 25380056
[TBL] [Abstract][Full Text] [Related]
17. White matter volume in the brainstem and inferior parietal lobule is related to motor performance in children with autism spectrum disorder: A voxel-based morphometry study.
Hanaie R; Mohri I; Kagitani-Shimono K; Tachibana M; Matsuzaki J; Hirata I; Nagatani F; Watanabe Y; Fujita N; Taniike M
Autism Res; 2016 Sep; 9(9):981-92. PubMed ID: 26808675
[TBL] [Abstract][Full Text] [Related]
18. Automated identification of postural control for children with autism spectrum disorder using a machine learning approach.
Li Y; Mache MA; Todd TA
J Biomech; 2020 Dec; 113():110073. PubMed ID: 33142203
[TBL] [Abstract][Full Text] [Related]
19. Diagnostic classification of intrinsic functional connectivity highlights somatosensory, default mode, and visual regions in autism.
Chen CP; Keown CL; Jahedi A; Nair A; Pflieger ME; Bailey BA; Müller RA
Neuroimage Clin; 2015; 8():238-45. PubMed ID: 26106547
[TBL] [Abstract][Full Text] [Related]
20. Interpersonal motor coordination during joint actions in children with and without autism spectrum disorder: The role of motor information.
Fulceri F; Tonacci A; Lucaferro A; Apicella F; Narzisi A; Vincenti G; Muratori F; Contaldo A
Res Dev Disabil; 2018 Sep; 80():13-23. PubMed ID: 29879613
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]