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For: Chaim-Avancini TM, Doshi J, Zanetti MV, Erus G, Silva MA, Duran FLS, Cavallet M, Serpa MH, Caetano SC, Louza MR, Davatzikos C, Busatto GF. Neurobiological support to the diagnosis of ADHD in stimulant-naïve adults: pattern recognition analyses of MRI data. Acta Psychiatr Scand 2017;136:623-36. [PMID: 29080396 DOI: 10.1111/acps.12824] [Cited by in Crossref: 10] [Cited by in F6Publishing: 8] [Article Influence: 2.0] [Reference Citation Analysis]
Number Citing Articles
1 Ekman E, Hiltunen A, Gustafsson H. Do Athletes Have More of a Cognitive Profile with ADHD Criteria than Non-Athletes? Sports (Basel) 2021;9:61. [PMID: 34064644 DOI: 10.3390/sports9050061] [Reference Citation Analysis]
2 Luo Y, Alvarez TL, Halperin JM, Li X. Multimodal neuroimaging-based prediction of adult outcomes in childhood-onset ADHD using ensemble learning techniques. Neuroimage Clin 2020;26:102238. [PMID: 32182578 DOI: 10.1016/j.nicl.2020.102238] [Cited by in Crossref: 6] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
3 Busatto Filho G, Rosa PG, Serpa MH, Squarzoni P, Duran FL. Psychiatric neuroimaging research in Brazil: historical overview, current challenges, and future opportunities. Braz J Psychiatry 2020;43:83-101. [PMID: 32520165 DOI: 10.1590/1516-4446-2019-0757] [Reference Citation Analysis]
4 Loh HW, Ooi CP, Barua PD, Palmer EE, Molinari F, Acharya U. Automated detection of ADHD: Current trends and future perspective. Computers in Biology and Medicine 2022. [DOI: 10.1016/j.compbiomed.2022.105525] [Reference Citation Analysis]
5 Montaleão Brum Alves R, Ferreira da Silva M, Assis Schmitz É, Juarez Alencar A. Trends, Limits, and Challenges of Computer Technologies in Attention Deficit Hyperactivity Disorder Diagnosis and Treatment. Cyberpsychol Behav Soc Netw 2021. [PMID: 34569852 DOI: 10.1089/cyber.2020.0867] [Reference Citation Analysis]
6 Rashid B, Calhoun V. Towards a brain-based predictome of mental illness. Hum Brain Mapp. 2020;41:3468-3535. [PMID: 32374075 DOI: 10.1002/hbm.25013] [Cited by in Crossref: 15] [Cited by in F6Publishing: 18] [Article Influence: 7.5] [Reference Citation Analysis]
7 Zhang-James Y, Helminen EC, Liu J, Franke B, Hoogman M, Faraone SV; ENIGMA-ADHD Working Group. Evidence for similar structural brain anomalies in youth and adult attention-deficit/hyperactivity disorder: a machine learning analysis. Transl Psychiatry 2021;11:82. [PMID: 33526765 DOI: 10.1038/s41398-021-01201-4] [Cited by in Crossref: 9] [Cited by in F6Publishing: 7] [Article Influence: 9.0] [Reference Citation Analysis]
8 Sakai K, Yamada K. Machine learning studies on major brain diseases: 5-year trends of 2014–2018. Jpn J Radiol 2019;37:34-72. [DOI: 10.1007/s11604-018-0794-4] [Cited by in Crossref: 49] [Cited by in F6Publishing: 35] [Article Influence: 12.3] [Reference Citation Analysis]
9 Alam S, Raja P, Gulzar Y, Lakshmanna K. Investigation of Machine Learning Methods for Early Prediction of Neurodevelopmental Disorders in Children. Wireless Communications and Mobile Computing 2022;2022:1-12. [DOI: 10.1155/2022/5766386] [Reference Citation Analysis]
10 Bu X, Cao M, Huang X, He Y. The structural connectome in ADHD. Psychoradiology 2021;1:257-71. [DOI: 10.1093/psyrad/kkab021] [Reference Citation Analysis]