These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

131 related articles for article (PubMed ID: 38548002)

  • 1. Predicting treatment outcome based on resting-state functional connectivity in internalizing mental disorders: A systematic review and meta-analysis.
    Meinke C; Lueken U; Walter H; Hilbert K
    Neurosci Biobehav Rev; 2024 May; 160():105640. PubMed ID: 38548002
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Lack of evidence for predictive utility from resting state fMRI data for individual exposure-based cognitive behavioral therapy outcomes: A machine learning study in two large multi-site samples in anxiety disorders.
    Hilbert K; Böhnlein J; Meinke C; Chavanne AV; Langhammer T; Stumpe L; Winter N; Leenings R; Adolph D; Arolt V; Bischoff S; Cwik JC; Deckert J; Domschke K; Fydrich T; Gathmann B; Hamm AO; Heinig I; Herrmann MJ; Hollandt M; Hoyer J; Junghöfer M; Kircher T; Koelkebeck K; Lotze M; Margraf J; Mumm JLM; Neudeck P; Pauli P; Pittig A; Plag J; Richter J; Ridderbusch IC; Rief W; Schneider S; Schwarzmeier H; Seeger FR; Siminski N; Straube B; Straube T; Ströhle A; Wittchen HU; Wroblewski A; Yang Y; Roesmann K; Leehr EJ; Dannlowski U; Lueken U
    Neuroimage; 2024 Jul; 295():120639. PubMed ID: 38796977
    [TBL] [Abstract][Full Text] [Related]  

  • 3. PTSD and its dissociative subtype through the lens of the insula: Anterior and posterior insula resting-state functional connectivity and its predictive validity using machine learning.
    Harricharan S; Nicholson AA; Thome J; Densmore M; McKinnon MC; Théberge J; Frewen PA; Neufeld RWJ; Lanius RA
    Psychophysiology; 2020 Jan; 57(1):e13472. PubMed ID: 31502268
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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; 12(15):2878-2886. PubMed ID: 34282889
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Use of machine learning in predicting clinical response to transcranial magnetic stimulation in comorbid posttraumatic stress disorder and major depression: A resting state electroencephalography study.
    Zandvakili A; Philip NS; Jones SR; Tyrka AR; Greenberg BD; Carpenter LL
    J Affect Disord; 2019 Jun; 252():47-54. PubMed ID: 30978624
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Predicting Delayed Neurocognitive Recovery After Non-cardiac Surgery Using Resting-State Brain Network Patterns Combined With Machine Learning.
    Jiang Z; Cai Y; Zhang X; Lv Y; Zhang M; Li S; Lin G; Bao Z; Liu S; Gu W
    Front Aging Neurosci; 2021; 13():715517. PubMed ID: 34867266
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Machine learning for post-traumatic stress disorder identification utilizing resting-state functional magnetic resonance imaging.
    Saba T; Rehman A; Shahzad MN; Latif R; Bahaj SA; Alyami J
    Microsc Res Tech; 2022 Jun; 85(6):2083-2094. PubMed ID: 35088496
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Neonatal Amygdala Functional Connectivity at Rest in Healthy and Preterm Infants and Early Internalizing Symptoms.
    Rogers CE; Sylvester CM; Mintz C; Kenley JK; Shimony JS; Barch DM; Smyser CD
    J Am Acad Child Adolesc Psychiatry; 2017 Feb; 56(2):157-166. PubMed ID: 28117062
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Overall survival time prediction for high-grade glioma patients based on large-scale brain functional networks.
    Liu L; Zhang H; Wu J; Yu Z; Chen X; Rekik I; Wang Q; Lu J; Shen D
    Brain Imaging Behav; 2019 Oct; 13(5):1333-1351. PubMed ID: 30155788
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: A systematic review.
    Ibrahim B; Suppiah S; Ibrahim N; Mohamad M; Hassan HA; Nasser NS; Saripan MI
    Hum Brain Mapp; 2021 Jun; 42(9):2941-2968. PubMed ID: 33942449
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Functional connectivity of the anterior cingulate cortex predicts treatment outcome for rTMS in treatment-resistant depression at 3-month follow-up.
    Ge R; Downar J; Blumberger DM; Daskalakis ZJ; Vila-Rodriguez F
    Brain Stimul; 2020; 13(1):206-214. PubMed ID: 31668646
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Network and state specificity in connectivity-based predictions of individual behavior.
    Kraljević N; Langner R; Küppers V; Raimondo F; Patil KR; Eickhoff SB; Müller VI
    Hum Brain Mapp; 2024 Jun; 45(8):e26753. PubMed ID: 38864353
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A meta-analysis and systematic review of single vs. multimodal neuroimaging techniques in the classification of psychosis.
    Porter A; Fei S; Damme KSF; Nusslock R; Gratton C; Mittal VA
    Mol Psychiatry; 2023 Aug; 28(8):3278-3292. PubMed ID: 37563277
    [TBL] [Abstract][Full Text] [Related]  

  • 14. The alterations of brain functional connectivity networks in major depressive disorder detected by machine learning through multisite rs-fMRI data.
    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
    Behav Brain Res; 2022 Oct; 435():114058. PubMed ID: 35995263
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Machine learning in the prediction of depression treatment outcomes: a systematic review and meta-analysis.
    Sajjadian M; Lam RW; Milev R; Rotzinger S; Frey BN; Soares CN; Parikh SV; Foster JA; Turecki G; Müller DJ; Strother SC; Farzan F; Kennedy SH; Uher R
    Psychol Med; 2021 Dec; 51(16):2742-2751. PubMed ID: 35575607
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Predicting superagers by machine learning classification based on the functional brain connectome using resting-state functional magnetic resonance imaging.
    Park CH; Kim BR; Park HK; Lim SM; Kim E; Jeong JH; Kim GH
    Cereb Cortex; 2022 Sep; 32(19):4183-4190. PubMed ID: 34969093
    [TBL] [Abstract][Full Text] [Related]  

  • 17. The predictive accuracy of machine learning for the risk of death in HIV patients: a systematic review and meta-analysis.
    Li Y; Feng Y; He Q; Ni Z; Hu X; Feng X; Ni M
    BMC Infect Dis; 2024 May; 24(1):474. PubMed ID: 38711068
    [TBL] [Abstract][Full Text] [Related]  

  • 18. The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features.
    Cui Z; Gong G
    Neuroimage; 2018 Sep; 178():622-637. PubMed ID: 29870817
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Machine learning prediction of cognition from functional connectivity: Are feature weights reliable?
    Tian Y; Zalesky A
    Neuroimage; 2021 Dec; 245():118648. PubMed ID: 34673248
    [TBL] [Abstract][Full Text] [Related]  

  • 20. An Assessment of the Predictive Performance of Current Machine Learning-Based Breast Cancer Risk Prediction Models: Systematic Review.
    Gao Y; Li S; Jin Y; Zhou L; Sun S; Xu X; Li S; Yang H; Zhang Q; Wang Y
    JMIR Public Health Surveill; 2022 Dec; 8(12):e35750. PubMed ID: 36426919
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.