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Cited by in F6Publishing
For: Yang J, Zhang M, Ahn H, Zhang Q, Jin TB, Li I, Nemesure M, Joshi N, Jiang H, Miller JM, Ogden RT, Petkova E, Milak MS, Sublette ME, Sullivan GM, Trivedi MH, Weissman M, McGrath PJ, Fava M, Kurian BT, Pizzagalli DA, Cooper CM, McInnis M, Oquendo MA, Mann JJ, Parsey RV, DeLorenzo C. Development and evaluation of a multimodal marker of major depressive disorder. Hum Brain Mapp 2018;39:4420-39. [PMID: 30113112 DOI: 10.1002/hbm.24282] [Cited by in Crossref: 14] [Cited by in F6Publishing: 14] [Article Influence: 3.5] [Reference Citation Analysis]
Number Citing Articles
1 Sun K, Liu Z, Chen G, Zhou Z, Zhong S, Tang Z, Wang S, Zhou G, Zhou X, Shao L, Ye X, Zhang Y, Jia Y, Pan J, Huang L, Liu X, Liu J, Tian J, Wang Y. A two-center radiomic analysis for differentiating major depressive disorder using multi-modality MRI data under different parcellation methods. J Affect Disord 2021;300:1-9. [PMID: 34942222 DOI: 10.1016/j.jad.2021.12.065] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
2 Steffens DC, Wang L, Pearlson GD. Functional connectivity predictors of acute depression treatment outcome. Int Psychogeriatr 2019;31:1831-5. [PMID: 30602399 DOI: 10.1017/S1041610218002260] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 2.0] [Reference Citation Analysis]
3 Klöbl M, Gryglewski G, Rischka L, Godbersen GM, Unterholzner J, Reed MB, Michenthaler P, Vanicek T, Winkler-Pjrek E, Hahn A, Kasper S, Lanzenberger R. Predicting Antidepressant Citalopram Treatment Response via Changes in Brain Functional Connectivity After Acute Intravenous Challenge. Front Comput Neurosci 2020;14:554186. [PMID: 33123000 DOI: 10.3389/fncom.2020.554186] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 1.5] [Reference Citation Analysis]
4 Hong S, Liu YS, Cao B, Cao J, Ai M, Chen J, Greenshaw A, Kuang L. Identification of suicidality in adolescent major depressive disorder patients using sMRI: A machine learning approach. J Affect Disord 2021;280:72-6. [PMID: 33202340 DOI: 10.1016/j.jad.2020.10.077] [Cited by in Crossref: 3] [Cited by in F6Publishing: 5] [Article Influence: 1.5] [Reference Citation Analysis]
5 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: 1] [Article Influence: 1.0] [Reference Citation Analysis]
6 Chen Z, Huang X, Gong Q, Biswal BB. Translational application of neuroimaging in major depressive disorder: a review of psychoradiological studies. Front Med 2021;15:528-40. [PMID: 33511554 DOI: 10.1007/s11684-020-0798-1] [Reference Citation Analysis]
7 Sen K, Anderson AA, Whitehead MT, Gropman AL. Review of Multi-Modal Imaging in Urea Cycle Disorders: The Old, the New, the Borrowed, and the Blue. Front Neurol 2021;12:632307. [PMID: 33995244 DOI: 10.3389/fneur.2021.632307] [Reference Citation Analysis]
8 Jiang X, Zhou C, Ao N, Gu W, Li J, Chen Y. Scarcity Mindset Neuro Network Decoding With Reward: A Tree-Based Model and Functional Near-Infrared Spectroscopy Study. Front Hum Neurosci 2021;15:736415. [PMID: 34899213 DOI: 10.3389/fnhum.2021.736415] [Reference Citation Analysis]
9 Stolicyn A, Harris MA, Shen X, Barbu MC, Adams MJ, Hawkins EL, de Nooij L, Yeung HW, Murray AD, Lawrie SM, Steele JD, McIntosh AM, Whalley HC. Automated classification of depression from structural brain measures across two independent community-based cohorts. Hum Brain Mapp 2020;41:3922-37. [PMID: 32558996 DOI: 10.1002/hbm.25095] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]
10 Yang J, Zhang M, Ahn H, Zhang Q, Jin TB, Li I, Nemesure M, Joshi N, Jiang H, Miller JM, Ogden RT, Petkova E, Milak MS, Sublette ME, Sullivan GM, Trivedi MH, Weissman M, McGrath PJ, Fava M, Kurian BT, Pizzagalli DA, Cooper CM, McInnis M, Oquendo MA, Mann JJ, Parsey RV, DeLorenzo C. Development and evaluation of a multimodal marker of major depressive disorder. Hum Brain Mapp 2018;39:4420-39. [PMID: 30113112 DOI: 10.1002/hbm.24282] [Cited by in Crossref: 14] [Cited by in F6Publishing: 14] [Article Influence: 3.5] [Reference Citation Analysis]
11 Al-hakeim HK, Al-fadhel SZ, Al-dujaili AH, Carvalho A, Sriswasdi S, Maes M. Development of a Novel Neuro-immune and Opioid-Associated Fingerprint with a Cross-Validated Ability to Identify and Authenticate Unknown Patients with Major Depression: Far Beyond Differentiation, Discrimination, and Classification. Mol Neurobiol 2019;56:7822-35. [DOI: 10.1007/s12035-019-01647-0] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 1.7] [Reference Citation Analysis]
12 Lozupone M, La Montagna M, D'Urso F, Daniele A, Greco A, Seripa D, Logroscino G, Bellomo A, Panza F. The Role of Biomarkers in Psychiatry. Adv Exp Med Biol 2019;1118:135-62. [PMID: 30747421 DOI: 10.1007/978-3-030-05542-4_7] [Cited by in Crossref: 13] [Cited by in F6Publishing: 8] [Article Influence: 4.3] [Reference Citation Analysis]
13 Thakre TP, Kulkarni H, Adams KS, Mischel R, Hayes R, Pandurangi A. Polysomnographic identification of anxiety and depression using deep learning. Journal of Psychiatric Research 2022;150:54-63. [DOI: 10.1016/j.jpsychires.2022.03.027] [Reference Citation Analysis]
14 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]
15 Lin Q, Zhu FY, Shu YQ, Zhu PW, Ye L, Shi WQ, Min YL, Li B, Yuan Q, Shao Y. Altered brain network centrality in middle-aged patients with retinitis pigmentosa: A resting-state functional magnetic resonance imaging study. Brain Behav 2021;11:e01983. [PMID: 33295117 DOI: 10.1002/brb3.1983] [Reference Citation Analysis]
16 Faria AV, Zhao Y, Ye C, Hsu J, Yang K, Cifuentes E, Wang L, Mori S, Miller M, Caffo B, Sawa A. Multimodal MRI assessment for first episode psychosis: A major change in the thalamus and an efficient stratification of a subgroup. Hum Brain Mapp 2021;42:1034-53. [PMID: 33377594 DOI: 10.1002/hbm.25276] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
17 Zhang YD, Dong Z, Wang SH, Yu X, Yao X, Zhou Q, Hu H, Li M, Jiménez-Mesa C, Ramirez J, Martinez FJ, Gorriz JM. Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation. Inf Fusion 2020;64:149-87. [PMID: 32834795 DOI: 10.1016/j.inffus.2020.07.006] [Cited by in Crossref: 36] [Cited by in F6Publishing: 9] [Article Influence: 18.0] [Reference Citation Analysis]
18 Chen YL, Tu PC, Huang TH, Bai YM, Su TP, Chen MH, Wu YT. Identifying subtypes of bipolar disorder based on clinical and neurobiological characteristics. Sci Rep 2021;11:17082. [PMID: 34429498 DOI: 10.1038/s41598-021-96645-5] [Reference Citation Analysis]
19 Dotson VM, Bogoian HR, Gradone AM, Taiwo Z, Minto LR. Subthreshold depressive symptoms relate to cuneus structure: Thickness asymmetry and sex differences. J Psychiatr Res 2021;145:144-7. [PMID: 34922098 DOI: 10.1016/j.jpsychires.2021.12.013] [Reference Citation Analysis]