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For: Ma Q, Zhang T, Zanetti MV, Shen H, Satterthwaite TD, Wolf DH, Gur RE, Fan Y, Hu D, Busatto GF, Davatzikos C. Classification of multi-site MR images in the presence of heterogeneity using multi-task learning. Neuroimage Clin 2018;19:476-86. [PMID: 29984156 DOI: 10.1016/j.nicl.2018.04.037] [Cited by in Crossref: 16] [Cited by in F6Publishing: 17] [Article Influence: 4.0] [Reference Citation Analysis]
Number Citing Articles
1 Leming M, Das S, Im H. Construction of a confounder-free clinical MRI dataset in the Mass General Brigham system for classification of Alzheimer's disease. Artificial Intelligence in Medicine 2022;129:102309. [DOI: 10.1016/j.artmed.2022.102309] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
2 Devi Priya R, Sivaraj R, Anitha N, Devisurya V. Tri-Staged feature selection in Multi-class Heterogeneous datasets using Memetic algorithm and Cuckoo Search Optimization. Expert Systems with Applications 2022. [DOI: 10.1016/j.eswa.2022.118286] [Reference Citation Analysis]
3 Jiao Z, Chen S, Shi H, Xu J. Multi-Modal Feature Selection with Feature Correlation and Feature Structure Fusion for MCI and AD Classification. Brain Sciences 2022;12:80. [DOI: 10.3390/brainsci12010080] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 6.0] [Reference Citation Analysis]
4 Lu M, Zhao Q, Zhang J, Pohl KM, Fei-Fei L, Niebles JC, Adeli E. Metadata Normalization. Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit 2021;2021:10912-22. [PMID: 34776724 DOI: 10.1109/cvpr46437.2021.01077] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
5 Eitel F, Schulz MA, Seiler M, Walter H, Ritter K. Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research. Exp Neurol 2021;339:113608. [PMID: 33513353 DOI: 10.1016/j.expneurol.2021.113608] [Cited by in F6Publishing: 5] [Reference Citation Analysis]
6 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. Biotypes of major depressive disorder: Neuroimaging evidence from resting-state default mode network patterns. Neuroimage Clin 2020;28:102514. [PMID: 33396001 DOI: 10.1016/j.nicl.2020.102514] [Cited by in Crossref: 3] [Cited by in F6Publishing: 11] [Article Influence: 1.5] [Reference Citation Analysis]
7 Garcia-Dias R, Scarpazza C, Baecker L, Vieira S, Pinaya WHL, Corvin A, Redolfi A, Nelson B, Crespo-Facorro B, McDonald C, Tordesillas-Gutiérrez D, Cannon D, Mothersill D, Hernaus D, Morris D, Setien-Suero E, Donohoe G, Frisoni G, Tronchin G, Sato J, Marcelis M, Kempton M, van Haren NEM, Gruber O, McGorry P, Amminger P, McGuire P, Gong Q, Kahn RS, Ayesa-Arriola R, van Amelsvoort T, Ortiz-García de la Foz V, Calhoun V, Cahn W, Mechelli A. Neuroharmony: A new tool for harmonizing volumetric MRI data from unseen scanners. Neuroimage 2020;220:117127. [PMID: 32634595 DOI: 10.1016/j.neuroimage.2020.117127] [Cited by in Crossref: 12] [Cited by in F6Publishing: 16] [Article Influence: 6.0] [Reference Citation Analysis]
8 Jin D, Zhou B, Han Y, Ren J, Han T, Liu B, Lu J, Song C, Wang P, Wang D, Xu J, Yang Z, Yao H, Yu C, Zhao K, Wintermark M, Zuo N, Zhang X, Zhou Y, Zhang X, Jiang T, Wang Q, Liu Y. Generalizable, Reproducible, and Neuroscientifically Interpretable Imaging Biomarkers for Alzheimer's Disease. Adv Sci (Weinh) 2020;7:2000675. [PMID: 32714766 DOI: 10.1002/advs.202000675] [Cited by in Crossref: 21] [Cited by in F6Publishing: 20] [Article Influence: 10.5] [Reference Citation Analysis]
9 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]
10 Chen T, Chen Y, Yuan M, Gerstein M, Li T, Liang H, Froehlich T, Lu L. The Development of a Practical Artificial Intelligence Tool for Diagnosing and Evaluating Autism Spectrum Disorder: Multicenter Study. JMIR Med Inform 2020;8:e15767. [PMID: 32041690 DOI: 10.2196/15767] [Cited by in Crossref: 7] [Cited by in F6Publishing: 11] [Article Influence: 3.5] [Reference Citation Analysis]
11 Lin T, Zhong R, Wang Y, Xu J, Jiang H, Xu J, Ying Y, Rodriguez L, Ting KC, Li H. DeepCropNet: a deep spatial-temporal learning framework for county-level corn yield estimation. Environ Res Lett 2020;15:034016. [DOI: 10.1088/1748-9326/ab66cb] [Cited by in Crossref: 16] [Cited by in F6Publishing: 10] [Article Influence: 8.0] [Reference Citation Analysis]
12 Li F, Wu D, Lui S, Gong Q, Sweeney JA. Clinical Strategies and Technical Challenges in Psychoradiology. Neuroimaging Clin N Am 2020;30:1-13. [PMID: 31759566 DOI: 10.1016/j.nic.2019.09.001] [Cited by in Crossref: 4] [Cited by in F6Publishing: 9] [Article Influence: 1.3] [Reference Citation Analysis]
13 George A, Kuzniecky R, Rusinek H, Pardoe HR; Human Epilepsy Project Investigators. Standardized Brain MRI Acquisition Protocols Improve Statistical Power in Multicenter Quantitative Morphometry Studies. J Neuroimaging 2020;30:126-33. [PMID: 31664774 DOI: 10.1111/jon.12673] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.7] [Reference Citation Analysis]
14 Xie Q, Shen W, Li Z, Baranova A, Cao H, Li Z. A core collection of pan-schizophrenia genes allows building cohort-specific signatures of affected brain. Sci Rep 2019;9:12671. [PMID: 31481672 DOI: 10.1038/s41598-019-48605-3] [Reference Citation Analysis]
15 Ashburner J, Brudfors M, Bronik K, Balbastre Y. An algorithm for learning shape and appearance models without annotations. Med Image Anal 2019;55:197-215. [PMID: 31096134 DOI: 10.1016/j.media.2019.04.008] [Cited by in Crossref: 4] [Article Influence: 1.3] [Reference Citation Analysis]
16 Salman MS, Du Y, Lin D, Fu Z, Fedorov A, Damaraju E, Sui J, Chen J, Mayer AR, Posse S, Mathalon DH, Ford JM, Van Erp T, Calhoun VD. Group ICA for identifying biomarkers in schizophrenia: 'Adaptive' networks via spatially constrained ICA show more sensitivity to group differences than spatio-temporal regression. Neuroimage Clin 2019;22:101747. [PMID: 30921608 DOI: 10.1016/j.nicl.2019.101747] [Cited by in Crossref: 41] [Cited by in F6Publishing: 36] [Article Influence: 13.7] [Reference Citation Analysis]
17 Luo Z, Hou C, Wang L, Hu D. Gender Identification of Human Cortical 3-D Morphology Using Hierarchical Sparsity. Front Hum Neurosci 2019;13:29. [PMID: 30792634 DOI: 10.3389/fnhum.2019.00029] [Cited by in Crossref: 5] [Cited by in F6Publishing: 7] [Article Influence: 1.7] [Reference Citation Analysis]