Publications by Vega, Roberto
In Journal (refereed)
1. | S. Liang, R. Vega, X. Kong, W. Deng, Q. Wang, M. Li, X. Hu, A. Greenshaw, R. Greiner, T. Li. "Neurocognitive Graphs of First-Episode Schizophrenia and Major Depression Based on Cognitive Features". Neuroscience Bulletin, 34(2), pp 312-320, April 2018. |
2. | F. Seyednasrollah, D. Koestler, T. Wang, S. Piccolo, R. Vega, R. Greiner, C. Fuchs, E. Gofer, L. Kumar. "A DREAM Challenge to build prediction models for short-term discontinuation of docetaxel in metastatic castration-resistant prostate cancer". Journal of Clinical Oncology: Clinical Cancer Informatics, (1), pp 1-15, July 2017. |
3. | J. Guinney, T. Wang, P. DREAM Community, R. Greiner, R. Vega, L. Kumar, J. Patel. "Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowd-sourced challenge with open clinical trial data.". Lancet Oncology, 18(1), pp 132-142, January 2017. |
4. | R. Vega, T. Sajed, K. Mathewson, K. Khare, P. Pilarski, R. Greiner, G. Sanchez-Ante, J. Antelis. "Assessment of feature selection and classification methods for recognizing motor imagery tasks from electroencephalographic signals". Artificial Intelligence Research, 6(1), pp 37-51, September 2016. |
In Conference (refereed)
5. | R. Vega, P. Gorji, Z. Zhang, X. Qin, A. Hareendranathan, J. Kapur, J. Jaremko, R. Greiner. "Sample Efficient Learning of Image-Based Diagnostic Classifiers". Artificial Intelligence and Statistics, March 2021. |
In Workshop
6. | R. Vega, R. Greiner. "Finding Effective Ways to (Machine) Learn fMRI-based Classifiers from Multi-Site Data". Machine Learning in Clinical Neuroimaging (MLCN), Springer, Cham, (ed: Stoyanov D. et al.), 11038, pp 32-39, October 2018. |
Other Categories
7. | R. Vega. "The challenge of applying machine learning techniques to diagnose schizophrenia using multi-site fMRI data". MSc Thesis, University of Alberta, January 2017. |