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For: Yamashita A, Sakai Y, Yamada T, Yahata N, Kunimatsu A, Okada N, Itahashi T, Hashimoto R, Mizuta H, Ichikawa N, Takamura M, Okada G, Yamagata H, Harada K, Matsuo K, Tanaka SC, Kawato M, Kasai K, Kato N, Takahashi H, Okamoto Y, Yamashita O, Imamizu H. Generalizable brain network markers of major depressive disorder across multiple imaging sites. PLoS Biol 2020;18:e3000966. [PMID: 33284797 DOI: 10.1371/journal.pbio.3000966] [Cited by in Crossref: 24] [Cited by in F6Publishing: 25] [Article Influence: 8.0] [Reference Citation Analysis]
Number Citing Articles
1 Okada G, Sakai Y, Shibakawa M, Yoshioka T, Itai E, Shinzato H, Yamamoto O, Kurata K, Tamura T, Jitsuiki H, Yamashita H, Mantani A, Yokota N, Kawato M, Okamoto Y. Examining the usefulness of the brain network marker program using fMRI for the diagnosis and stratification of major depressive disorder: a non-randomized study protocol. BMC Psychiatry 2023;23:63. [PMID: 36694153 DOI: 10.1186/s12888-023-04560-y] [Reference Citation Analysis]
2 Bondi E, Maggioni E, Brambilla P, Delvecchio G. A systematic review on the potential use of machine learning to classify major depressive disorder from healthy controls using resting state fMRI measures. Neurosci Biobehav Rev 2023;144:104972. [PMID: 36436736 DOI: 10.1016/j.neubiorev.2022.104972] [Reference Citation Analysis]
3 Kishimoto T, Nakamura H, Kano Y, Eguchi Y, Kitazawa M, Liang K, Kudo K, Sento A, Takamiya A, Horigome T, Yamasaki T, Sunami Y, Kikuchi T, Nakajima K, Tomita M, Bun S, Momota Y, Sawada K, Murakami J, Takahashi H, Mimura M. Understanding psychiatric illness through natural language processing (UNDERPIN): Rationale, design, and methodology. Front Psychiatry 2022;13. [DOI: 10.3389/fpsyt.2022.954703] [Reference Citation Analysis]
4 Barua PD, Vicnesh J, Lih OS, Palmer EE, Yamakawa T, Kobayashi M, Acharya UR. Artificial intelligence assisted tools for the detection of anxiety and depression leading to suicidal ideation in adolescents: a review. Cogn Neurodyn 2022. [DOI: 10.1007/s11571-022-09904-0] [Reference Citation Analysis]
5 Cao XJ, Liu XQ. Artificial intelligence-assisted psychosis risk screening in adolescents: Practices and challenges. World J Psychiatry 2022; 12(10): 1287-1297 [DOI: 10.5498/wjp.v12.i10.1287] [Reference Citation Analysis]
6 Wu H, Liu R, Zhou J, Feng L, Wang Y, Chen X, Zhang Z, Cui J, Zhou Y, Wang G. Prediction of remission among patients with a major depressive disorder based on the resting-state functional connectivity of emotion regulation networks. Transl Psychiatry 2022;12. [DOI: 10.1038/s41398-022-02152-0] [Reference Citation Analysis]
7 Lee J, Chi S, Lee M. Personalized Diagnosis and Treatment for Neuroimaging in Depressive Disorders. JPM 2022;12:1403. [DOI: 10.3390/jpm12091403] [Reference Citation Analysis]
8 Sawada M, Adolphs R, Dlouhy BJ, Jenison RL, Rhone AE, Kovach CK, Greenlee JDW, Howard Iii MA, Oya H. Mapping effective connectivity of human amygdala subdivisions with intracranial stimulation. Nat Commun 2022;13:4909. [PMID: 35987994 DOI: 10.1038/s41467-022-32644-y] [Reference Citation Analysis]
9 Dai P, Xiong T, Zhou X, Ou Y, Li Y, Kui X, Chen Z, Zou B, Li W, Huang Z, The Rest-Meta-Mdd Consortium. The alterations of brain functional connectivity networks in major depressive disorder detected by machine learning through multisite rs-fMRI data. Behav Brain Res 2022;435:114058. [PMID: 35995263 DOI: 10.1016/j.bbr.2022.114058] [Reference Citation Analysis]
10 Liu Z, Si L, Wang T, Wang G. Brain connectivity changes of propofol-induced altered states of consciousness using High-Density EEG Source Estimation. 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) 2022. [DOI: 10.1109/embc48229.2022.9871256] [Reference Citation Analysis]
11 Zheng K, Lu H, Wu Y, Wang H, Hu D, Chen B, Li B, the DIRECT consortium. Redefining and subtyping of major depression based on brain functional connectivity signatures with high generalization: an ensemble hybrid framework.. [DOI: 10.1101/2022.06.07.495073] [Reference Citation Analysis]
12 Li Y, Zhou Z, Li Q, Li T, Julian IN, Guo H, Chen J. Depression Classification Using Frequent Subgraph Mining Based on Pattern Growth of Frequent Edge in Functional Magnetic Resonance Imaging Uncertain Network. Front Neurosci 2022;16:889105. [DOI: 10.3389/fnins.2022.889105] [Reference Citation Analysis]
13 Qin K, Lei D, Pinaya WH, Pan N, Li W, Zhu Z, Sweeney JA, Mechelli A, Gong Q. Using graph convolutional network to characterize individuals with major depressive disorder across multiple imaging sites. eBioMedicine 2022;78:103977. [DOI: 10.1016/j.ebiom.2022.103977] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
14 Taylor JE, Yamada T, Kawashima T, Kobayashi Y, Yoshihara Y, Miyata J, Murai T, Kawato M, Motegi T. Depressive symptoms reduce when dorsolateral prefrontal cortex-precuneus connectivity normalizes after functional connectivity neurofeedback. Sci Rep 2022;12:2581. [PMID: 35173179 DOI: 10.1038/s41598-022-05860-1] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]
15 Liu J, Dey N, Crespo RG, Shi F, Liu C. Inadequate dataset learning for major depressive disorder MRI semantic classification. IET Image Processing 2022;16:1648-56. [DOI: 10.1049/ipr2.12437] [Reference Citation Analysis]
16 Bhadra S, Kumar CJ. An insight into diagnosis of depression using machine learning techniques: a systematic review. Curr Med Res Opin 2022;:1-62. [PMID: 35129401 DOI: 10.1080/03007995.2022.2038487] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
17 Velásquez MM, Gómez-Maquet Y, Ferro E, Cárdenas W, González-Nieves S, Lattig MC. Multidimensional Analysis of Major Depression: Association Between BDNF Methylation, Psychosocial and Cognitive Domains. Front Psychiatry 2021;12:768680. [PMID: 34970165 DOI: 10.3389/fpsyt.2021.768680] [Reference Citation Analysis]
18 Zhou Y, Si X, Chen Y, Chao Y, Lin CP, Li S, Zhang X, Ming D, Li Q. Hippocampus- and Thalamus-Related Fiber-Specific White Matter Reductions in Mild Cognitive Impairment. Cereb Cortex 2021:bhab407. [PMID: 34891164 DOI: 10.1093/cercor/bhab407] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
19 Seok D, Beer J, Jaskir M, Smyk N, Jaganjac A, Makhoul W, Cook P, Elliott M, Shinohara R, Sheline YI. Differential Impact of Anxious Misery Psychopathology on Multiple Representations of the Functional Connectome. Biological Psychiatry Global Open Science 2021. [DOI: 10.1016/j.bpsgos.2021.11.004] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
20 Itahashi T, Noda Y, Iwata Y, Tarumi R, Tsugawa S, Plitman E, Honda S, Caravaggio F, Kim J, Matsushita K, Gerretsen P, Uchida H, Remington G, Mimura M, Aoki YY, Graff-Guerrero A, Nakajima S. Dimensional distribution of cortical abnormality across antipsychotics treatment-resistant and responsive schizophrenia. Neuroimage Clin 2021;32:102852. [PMID: 34638035 DOI: 10.1016/j.nicl.2021.102852] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
21 Ogawa T, Moriya H, Hiroe N, Kawanabe M, Hirayama J. EEG-based neurofeedback with network components extraction: a data-driven approach by multilayer ICA extension and simultaneous EEG-fMRI measurements.. [DOI: 10.1101/2021.06.20.449196] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
22 Wang Y, Qin Y, Li H, Yao D, Sun B, Gong J, Dai Y, Wen C, Zhang L, Zhang C, Luo C, Zhu T. Identifying Internet Addiction and Evaluating the Efficacy of Treatment Based on Functional Connectivity Density: A Machine Learning Study. Front Neurosci 2021;15:665578. [PMID: 34220426 DOI: 10.3389/fnins.2021.665578] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
23 Yamashita A, Sakai Y, Yamada T, Yahata N, Kunimatsu A, Okada N, Itahashi T, Hashimoto R, Mizuta H, Ichikawa N, Takamura M, Okada G, Yamagata H, Harada K, Matsuo K, Tanaka SC, Kawato M, Kasai K, Kato N, Takahashi H, Okamoto Y, Yamashita O, Imamizu H. Common Brain Networks Between Major Depressive-Disorder Diagnosis and Symptoms of Depression That Are Validated for Independent Cohorts. Front Psychiatry 2021;12:667881. [PMID: 34177657 DOI: 10.3389/fpsyt.2021.667881] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
24 Tokuda T, Yamashita O, Yoshimoto J. Multiple clustering for identifying subject clusters and brain sub-networks using functional connectivity matrices without vectorization. Neural Netw 2021;142:269-87. [PMID: 34052471 DOI: 10.1016/j.neunet.2021.05.016] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 3.0] [Reference Citation Analysis]
25 Koike S, Tanaka SC, Okada T, Aso T, Yamashita A, Yamashita O, Asano M, Maikusa N, Morita K, Okada N, Fukunaga M, Uematsu A, Togo H, Miyazaki A, Murata K, Urushibata Y, Autio J, Ose T, Yoshimoto J, Araki T, Glasser MF, Van Essen DC, Maruyama M, Sadato N, Kawato M, Kasai K, Okamoto Y, Hanakawa T, Hayashi T; Brain/MINDS Beyond Human Brain MRI Group. Brain/MINDS beyond human brain MRI project: A protocol for multi-level harmonization across brain disorders throughout the lifespan. Neuroimage Clin 2021;30:102600. [PMID: 33741307 DOI: 10.1016/j.nicl.2021.102600] [Cited by in Crossref: 12] [Cited by in F6Publishing: 13] [Article Influence: 6.0] [Reference Citation Analysis]
26 Belov V, Kozyrev V, Singh A, Sacchet MD, Goya-maldonado R. Subject-specific whole-brain parcellations of nodes and boundaries are modulated differently under 10Hz rTMS.. [DOI: 10.1101/2021.03.09.434571] [Reference Citation Analysis]
27 Seok D, Beer J, Jaskir M, Smyk N, Jaganjac A, Makhoul W, Cook P, Elliott M, Shinohara R, Sheline YI. Differential impact of transdiagnostic, dimensional psychopathology on multiple scales of functional connectivity.. [DOI: 10.1101/2021.03.05.434151] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
28 Taylor JE, Yamada T, Kawashima T, Kobayashi Y, Yoshihara Y, Miyata J, Murai T, Kawato M, Motegi T. Reduction of brooding and more general depressive symptoms after fMRI neurofeedback targeting a melancholic functional-connectivity biomarker.. [DOI: 10.1101/2021.01.21.20248810] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
29 Taylor JE, Jalon I, Chiba T, Motegi T, Kawato M, Hendler T. Translation to the clinic and other modalities. fMRI Neurofeedback 2021. [DOI: 10.1016/b978-0-12-822421-2.00002-8] [Reference Citation Analysis]