Machine Learning

Bagging Ensembles for the Diagnosis and Prognostication of Alzheimer’s Disease, the Thirteenth
AAAI Conference on Artificial Intelligence (AAAI-16), P. Dai, F. Gwadry-Sridhar, M. Bauer, M. Borrie. Phoenix, Arizona, USA, 12-17 Feb, 2016. (Paper)

P. Dai, F. Gwadry-Sridhar, M. Bauer, M. Borrie, and X. Teng, Longitudinal Brain Structure Changes in Health/MCI Patients: A Deep Learning Approach for the Diagnosis and Prognosis of Alzheimer’s Disease, Alzheimer’s Association International Conference (AAIC), Toronto, ON, Canada, 24-27 July, 2016. (Poster)

X. Teng, P. Dai, F. Gwadry-Sridhar, M. Borrie, Clinical Feature Vs Artificial Intelligence Feature: Risk Factor Analysis Based on Deep Learning, Alzheimer’s Association International Conference (AAIC), Toronto, ON, Canada, 24-27 July, 2016. (Abstract)

P. Dai, F. Gwadry-Sridhar, M. Bauer, M. Borrie and X. Teng, Healthy Cognitive Aging: a hybrid random vector functional-link model for the analysis of Alzheimer’s disease, the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), San Francisco, California USA, 4-9 Feb, 2017. (Paper)

P. Dai, F. Gwadry-Sridhar, M. Bauer, and M. Borrie, Unveil the hidden Information behind the variables of Alzheimer’s disease (AD): a systematic comparison of Manifold Learning algorithms in AD, in 8th Canadian Conference on Dementia (CCD), Ottawa, Canada, 1-3 Oct, 2015. (Poster)

P. Dai, F. Gwadry-Sridhar, M. Bauer, and M. Borrie, Structural Differences in Cognitively Normal, Mild Cognitive Impairment, and Alzheimer’s Disease Individuals: Alzheimer’s & Dementia. July 2015, Volume 11, Issue 7, Supplement, Pages P879–P880 (Article)

S. Nikan, F. Gwadry-Sridhar, M. Bauer, Machine learning application to predict the risk of coronary artery atherosclerosis, The 2016 International Conference on Computational Science and Computational Intelligence (CSCI’16), Las Vegas, USA, Dec 2016. (In press)

S. Nikan, F. Gwadry-Sridhar, M. Bauer, Pattern recognition application in ECG arrhythmia classification, The 10th International Conference on Health Informatics (HEALTINF2017), Porto, Portugal, Feb 2017. (Accepted)

White JA, Kim HW, Shah D, Fine N, Kim KY, Wendell DC, Al-Jaroudi W, Parker M, Patel M, Gwadry-Sridhar F, Judd RM, Kim RJ. CMR Imaging With Rapid Visual T1 Assessment Predicts Mortality in Patients Suspected of Cardiac Amyloidosis. JACC: Cardiovascular Imaging. Feb 2014; 7(2): 143-156. (Paper)

Hamou A, Simmons A, Bauer M, Lewden B, Zhang Y, Wahlund L, Westman E, Pritchard M, Kloszewska I, Mecozzi P, Soininen H, Tsolaki M, Vellas B, Muehlboeck S, Evans A, Julin P, Sjögren N, Spenger C, Lovestone S, Gwadry-Sridhar F,and other participants in the AddNeuroMed Consortium. Cluster Analysis of MR Imaging in Alzheimer’s Disease using Decision Tree Refinement. International Journal of Artificial Intelligence. 2011 March; 6(11): 90-9. (Paper)

Gwadry-Sridhar F, Bauer M, Lewden B, Hamou A. A Markov analysis of patients developing sepsis using clusters. In Proceedings of the ECAI 2010 conference on Knowledge representation for health-care (KR4HC’10), Berlin, Heidelberg, 85-100. (Poster)