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Universal Screening for Autism in Toddlers

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Author Title [ Type(Desc)] Year
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Conference Paper
T. Watanabe, Tunc, B., Parker, D., Kim, J., and Verma, R., Label-Informed Non-negative Matrix Factorization with Manifold Regularization for Discriminative Subnetwork Detection, in International Conference on Medical Image Computing and Computer-Assisted Intervention, 2016.
M. Hauser, Sariyanidi, E., Tunc, B., Zampella, C., Brodkin, E., Schultz, R., and Parish-Morris, J., Using natural conversations to classify autism with limited data: Age matters, in Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology, Minneapolis, Minnesota, 2019.
M. Hauser, Sariyanidi, E., Tunc, B., Zampella, C., Brodkin, E., Schultz, R. T., and Parish-Morris, J., Using natural conversations to classify autism with limited data: Age matters, in Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology, 2019.
Journal Article
B. Solmaz, Tunc, B., Parker, D., Whyte, J., Hart, T., Rabinowitz, A., Rohrbach, M., Kim, J., and Verma, R., Assessing connectivity related injury burden in diffuse traumatic brain injury., Hum Brain Mapp, vol. 38, no. 6, pp. 2913-2922, 2017.
Y. Ghanbari, Bloy, L., Tunc, B., Shankar, V., Roberts, T. P. L., J Edgar, C., Schultz, R. T., and Verma, R., On characterizing population commonalities and subject variations in brain networks., Med Image Anal, vol. 38, pp. 215-229, 2017.
R. T. Shinohara, Shou, H., Carone, M., Schultz, R., Tunc, B., Parker, D., and Verma, R., Distance-Based Analysis of Variance for Brain Connectivity, 2016.
B. Tunc, Solmaz, B., Parker, D., Satterthwaite, T. D., Elliott, M. A., Calkins, M. E., Ruparel, K., Gur, R. E., Gur, R. C., and Verma, R., Establishing a link between sex-related differences in the structural connectome and behaviour., Philos Trans R Soc Lond B Biol Sci, vol. 371, no. 1688, p. 20150111, 2016.
B. E. Yerys, Tunc, B., Satterthwaite, T. D., Antezana, L., Mosner, M. G., Bertollo, J. R., Guy, L., Schultz, R. T., and Herrington, J. D., Functional Connectivity of Frontoparietal and Salience/Ventral Attention Networks Have Independent Associations With Co-occurring Attention-Deficit/Hyperactivity Disorder Symptoms in Children With Autism., Biol Psychiatry Cogn Neurosci Neuroimaging, vol. 4, no. 4, pp. 343-351, 2019.
J. - P. Fortin, Parker, D., Tunc, B., Watanabe, T., Elliott, M. A., Ruparel, K., Roalf, D. R., Satterthwaite, T. D., Gur, R. C., Gur, R. E., Schultz, R. T., Verma, R., and Shinohara, R. T., Harmonization of multi-site diffusion tensor imaging data., Neuroimage, vol. 161, pp. 149-170, 2017.
G. L. Baum, Roalf, D. R., Cook, P. A., Ciric, R., Rosen, A. F. G., Xia, C., Elliott, M. A., Ruparel, K., Verma, R., Tunc, B., Gur, R. C., Gur, R. E., Bassett, D. S., and Satterthwaite, T. D., The impact of in-scanner head motion on structural connectivity derived from diffusion MRI., Neuroimage, vol. 173, pp. 275-286, 2018.
B. Tunc, Ingalhalikar, M., Parker, D., Lecoeur, J., Singh, N., Wolf, R. L., Macyszyn, L., Brem, S., and Verma, R., Individualized Map of White Matter Pathways: Connectivity-Based Paradigm for Neurosurgical Planning., Neurosurgery, vol. 79, no. 4, pp. 568-77, 2016.
B. Tunc, Ghanbari, Y., Smith, A. R., Pandey, J., Browne, A., Schultz, R. T., and Verma, R., PUNCH: Population Characterization of Heterogeneity., Neuroimage, vol. 98, pp. 50-60, 2014.
B. Tunc, Semantics of object representation in machine learning, Pattern Recognition Letters, vol. 64, pp. 30–36, 2015.
N. Honnorat, Parker, D., Tunc, B., Davatzikos, C., and Verma, R., Subject-Specific Structural Parcellations Based on Randomized AB-divergences., Med Image Comput Comput Assist Interv, vol. 10433, pp. 407-415, 2017.
B. Tunc, Shankar, V., Parker, D., Schultz, R. T., and Verma, R., Towards a Quantified Network Portrait of a Population., Inf Process Med Imaging, vol. 24, pp. 650-61, 2015.
B. Tunc and Verma, R., Unifying Inference of Meso-Scale Structures in Networks., PLoS One, vol. 10, no. 11, p. e0143133, 2015.
F. Zhang, Savadjiev, P., Caí, W., Song, Y., Rathi, Y., Tunc, B., Parker, D., Kapur, T., Schultz, R. T., Makris, N., Verma, R., and O'Donnell, L. J., Whole brain white matter connectivity analysis using machine learning: An application to autism., Neuroimage, vol. 172, pp. 826-837, 2018.