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Publications in 2017

In Journal (refereed)

1. 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, July 2017. view
2. S. Liang, W. Deng, Q. Wang, M. Li, M. Juhas, X. Li, R. Greiner, A. Greenshaw, T. Li. "Convergence and divergence of neurocognitive patterns in schizophrenia and depression.". Schizophrenia Research, June 2017. view
3. M. Gheiratmand, I. Rish, G. Cecchi, M. Brown, R. Greiner, P. Bashivan, A. Greenshaw, R. Ramasubbu, S. Dursun. "Learning stable and predictive network-based patterns ofschizophrenia and its clinical symptoms". Nature Schizophrenia, May 2017. view
4. M. Gheiratmand, I. Rish, G. Cecchi, M. Brown, R. Greiner, P. Bashivan, P. Polosecki, S. Dursun. "Learning Discriminative Functional Network Features of Schizophrenia". SPIE Medical Imaging, April 2017. view
5. E. Ryan, J. Holland, E. Stroulia, B. Bazelli, S. Babwik, H. Li, P. Senior, R. Greiner. "Improved A1C with smart phone app use in Type 1 diabetes". Canadian Journal of Diabetes, 41(1), pp 33-40, February 2017. view
6. 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. view

In Conference (refereed)

7. S. Romansky, S. Chowdhury, A. Hindle, N. Borle, R. Greiner. "Deep Green: An Ensemble of Machine Learning Methods Predicting Mobile Energy Consumption". International Conference on Software Maintenance and Evolution, July 2017. view

In Workshop

8. J. Dakka, P. Bashivan, M. Gheiratmand, I. Rish, S. Jha, R. Greiner. "Learning Neural Markers of Schizophrenia Disorder Using Recurrent Neural Networks". NIPS workshop on Machine Learning for Health, pp 6, December 2017. view
9. N. Hassanpour, R. Greiner. "A Novel Evaluation Methodology for Assessing Off-Policy Learning Methods in Contextual Bandits [wkshp]". NIPS 2017 Workshop on Causal Inference and Machine Learning (WhatIF2017), November 2017. PDFview
10. M. Gheiratmand, I. Rish, G. Cecchi, M. Brown, R. Greiner, A. Greenshaw, S. Dursun. "Functional Network Patterns as Multivariate Predictors of Symptom Severity in Schizophrenia". 23nd Annual Meeting of the Organization for Human Brain Mapping, May 2017. view

Other Categories

11. N. Borle. "The Challenge of Predicting Future Blood Glucose for Patients with Type I Diabetes". MSc Thesis, University of Alberta, November 2017. PDFview
12. R. Vega. "The challenge of applying machine learning techniques to diagnose schizophrenia using multi-site fMRI data". MSc Thesis, University of Alberta, January 2017. PDFview
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