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Journal Abstract Search

187 related items for PubMed ID: 37467800

  • 21. Biotypes of major depressive disorder: Neuroimaging evidence from resting-state default mode network patterns.
    Liang S, Deng W, Li X, Greenshaw AJ, Wang Q, Li M, Ma X, Bai TJ, Bo QJ, Cao J, Chen GM, Chen W, Cheng C, Cheng YQ, Cui XL, Duan J, Fang YR, Gong QY, Guo WB, Hou ZH, Hu L, Kuang L, Li F, Li KM, Liu YS, Liu ZN, Long YC, Luo QH, Meng HQ, Peng DH, Qiu HT, Qiu J, Shen YD, Shi YS, Si TM, Wang CY, Wang F, Wang K, Wang L, Wang X, Wang Y, Wu XP, Wu XR, Xie CM, Xie GR, Xie HY, Xie P, Xu XF, Yang H, Yang J, Yu H, Yao JS, Yao SQ, Yin YY, Yuan YG, Zang YF, Zhang AX, Zhang H, Zhang KR, Zhang ZJ, Zhao JP, Zhou RB, Zhou YT, Zou CJ, Zuo XN, Yan CG, Li T.
    Neuroimage Clin; 2020; 28():102514. PubMed ID: 33396001
    [Abstract] [Full Text] [Related]

  • 22. Treatment-naïve first episode depression classification based on high-order brain functional network.
    Zheng Y, Chen X, Li D, Liu Y, Tan X, Liang Y, Zhang H, Qiu S, Shen D.
    J Affect Disord; 2019 Sep 01; 256():33-41. PubMed ID: 31158714
    [Abstract] [Full Text] [Related]

  • 23. Ensemble graph neural network model for classification of major depressive disorder using whole-brain functional connectivity.
    Venkatapathy S, Votinov M, Wagels L, Kim S, Lee M, Habel U, Ra IH, Jo HG.
    Front Psychiatry; 2023 Sep 01; 14():1125339. PubMed ID: 37032921
    [Abstract] [Full Text] [Related]

  • 24. Effective hyper-connectivity network construction and learning: Application to major depressive disorder identification.
    Liu J, Yang W, Ma Y, Dong Q, Li Y, Hu B, DIRECT Consortium.
    Comput Biol Med; 2024 Mar 01; 171():108069. PubMed ID: 38394798
    [Abstract] [Full Text] [Related]

  • 25.
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  • 26. Classification of Major Depressive Disorder Based on Integrated Temporal and Spatial Functional MRI Variability Features of Dynamic Brain Network.
    Gai Q, Chu T, Che K, Li Y, Dong F, Zhang H, Li Q, Ma H, Shi Y, Zhao F, Liu J, Mao N, Xie H.
    J Magn Reson Imaging; 2023 Sep 01; 58(3):827-837. PubMed ID: 36579618
    [Abstract] [Full Text] [Related]

  • 27. Altered resting-state dynamic functional brain networks in major depressive disorder: Findings from the REST-meta-MDD consortium.
    Long Y, Cao H, Yan C, Chen X, Li L, Castellanos FX, Bai T, Bo Q, Chen G, Chen N, Chen W, Cheng C, Cheng Y, Cui X, Duan J, Fang Y, Gong Q, Guo W, Hou Z, Hu L, Kuang L, Li F, Li K, Li T, Liu Y, Luo Q, Meng H, Peng D, Qiu H, Qiu J, Shen Y, Shi Y, Si T, Wang C, Wang F, Wang K, Wang L, Wang X, Wang Y, Wu X, Wu X, Xie C, Xie G, Xie H, Xie P, Xu X, Yang H, Yang J, Yao J, Yao S, Yin Y, Yuan Y, Zhang A, Zhang H, Zhang K, Zhang L, Zhang Z, Zhou R, Zhou Y, Zhu J, Zou C, Zang Y, Zhao J, Kin-Yuen Chan C, Pu W, Liu Z.
    Neuroimage Clin; 2020 Sep 01; 26():102163. PubMed ID: 31953148
    [Abstract] [Full Text] [Related]

  • 28. Classification of Major Depressive Disorder from Resting-State fMRI.
    Sen B, Mueller B, Klimes-Dougan B, Cullen K, Parhi KK.
    Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul 01; 2019():3511-3514. PubMed ID: 31946635
    [Abstract] [Full Text] [Related]

  • 29. Spatio-temporal graph convolutional network for diagnosis and treatment response prediction of major depressive disorder from functional connectivity.
    Kong Y, Gao S, Yue Y, Hou Z, Shu H, Xie C, Zhang Z, Yuan Y.
    Hum Brain Mapp; 2021 Aug 15; 42(12):3922-3933. PubMed ID: 33969930
    [Abstract] [Full Text] [Related]

  • 30. Resting-state functional connectivity graph-properties correlate with bipolar disorder-risk in young medication-free depressed subjects: Bipolar-risk Resting State Functional Connectivity in Major Depression.
    Cha J, Spielberg JM, Hu B, Altinay M, Anand A.
    J Affect Disord; 2022 Mar 15; 301():52-59. PubMed ID: 35007643
    [Abstract] [Full Text] [Related]

  • 31. Altered brain dynamic in major depressive disorder: state and trait features.
    Javaheripour N, Colic L, Opel N, Li M, Maleki Balajoo S, Chand T, Van der Meer J, Krylova M, Izyurov I, Meller T, Goltermann J, Winter NR, Meinert S, Grotegerd D, Jansen A, Alexander N, Usemann P, Thomas-Odenthal F, Evermann U, Wroblewski A, Brosch K, Stein F, Hahn T, Straube B, Krug A, Nenadić I, Kircher T, Croy I, Dannlowski U, Wagner G, Walter M.
    Transl Psychiatry; 2023 Jul 17; 13(1):261. PubMed ID: 37460460
    [Abstract] [Full Text] [Related]

  • 32. Common and unique neural activities in subclinical depression and major depressive disorder indicate the development of brain impairments in different depressive stages.
    Zhang B, Liu S, Chen S, Yan F, Ke Y, Chen L, Ming D, Qi S, Wei X.
    J Affect Disord; 2022 Nov 15; 317():278-286. PubMed ID: 36057285
    [Abstract] [Full Text] [Related]

  • 33. Multivariate Machine Learning Analyses in Identification of Major Depressive Disorder Using Resting-State Functional Connectivity: A Multicentral Study.
    Shi Y, Zhang L, Wang Z, Lu X, Wang T, Zhou D, Zhang Z.
    ACS Chem Neurosci; 2021 Aug 04; 12(15):2878-2886. PubMed ID: 34282889
    [Abstract] [Full Text] [Related]

  • 34. Multi-feature concatenation and multi-classifier stacking: An interpretable and generalizable machine learning method for MDD discrimination with rsfMRI.
    Luo Y, Chen W, Zhan L, Qiu J, Jia T.
    Neuroimage; 2024 Jan 04; 285():120497. PubMed ID: 38142755
    [Abstract] [Full Text] [Related]

  • 35. A systematic review on the potential use of machine learning to classify major depressive disorder from healthy controls using resting state fMRI measures.
    Bondi E, Maggioni E, Brambilla P, Delvecchio G.
    Neurosci Biobehav Rev; 2023 Jan 04; 144():104972. PubMed ID: 36436736
    [Abstract] [Full Text] [Related]

  • 36. Depression recurrence is accompanied by longer periods in default mode and more frequent attentional and reward processing dynamic brain-states during resting-state activity.
    Alonso S, Tyborowska A, Ikani N, Mocking RJT, Figueroa CA, Schene AH, Deco G, Kringelbach ML, Cabral J, Ruhé HG.
    Hum Brain Mapp; 2023 Dec 01; 44(17):5770-5783. PubMed ID: 37672593
    [Abstract] [Full Text] [Related]

  • 37. Co-alteration Network Architecture of Major Depressive Disorder: A Multi-modal Neuroimaging Assessment of Large-scale Disease Effects.
    Gray JP, Manuello J, Alexander-Bloch AF, Leonardo C, Franklin C, Choi KS, Cauda F, Costa T, Blangero J, Glahn DC, Mayberg HS, Fox PT.
    Neuroinformatics; 2023 Apr 01; 21(2):443-455. PubMed ID: 36469193
    [Abstract] [Full Text] [Related]

  • 38. Aberrant brain network topology in fronto-limbic circuitry differentiates euthymic bipolar disorder from recurrent major depressive disorder.
    Dvorak J, Hilke M, Trettin M, Wenzler S, Hagen M, Ghirmai N, Müller M, Kraft D, Reif A, Oertel V.
    Brain Behav; 2019 Jun 01; 9(6):e01257. PubMed ID: 31066228
    [Abstract] [Full Text] [Related]

  • 39. Altered dynamic functional connectivity in weakly-connected state in major depressive disorder.
    Yao Z, Shi J, Zhang Z, Zheng W, Hu T, Li Y, Yu Y, Zhang Z, Fu Y, Zou Y, Zhang W, Wu X, Hu B.
    Clin Neurophysiol; 2019 Nov 01; 130(11):2096-2104. PubMed ID: 31541987
    [Abstract] [Full Text] [Related]

  • 40. Functional connectivity signatures of major depressive disorder: machine learning analysis of two multicenter neuroimaging studies.
    Gallo S, El-Gazzar A, Zhutovsky P, Thomas RM, Javaheripour N, Li M, Bartova L, Bathula D, Dannlowski U, Davey C, Frodl T, Gotlib I, Grimm S, Grotegerd D, Hahn T, Hamilton PJ, Harrison BJ, Jansen A, Kircher T, Meyer B, Nenadić I, Olbrich S, Paul E, Pezawas L, Sacchet MD, Sämann P, Wagner G, Walter H, Walter M, PsyMRI, van Wingen G.
    Mol Psychiatry; 2023 Jul 01; 28(7):3013-3022. PubMed ID: 36792654
    [Abstract] [Full Text] [Related]

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