Search For:

Displaying 1-6 out of 6 total
A Sparse Structure Learning Algorithm for Gaussian Bayesian Network Identification from High-Dimensional Data
Found in: IEEE Transactions on Pattern Analysis and Machine Intelligence
By Shuai Huang,Jing Li,Jieping Ye,Adam Fleisher,Kewei Chen,Teresa Wu,Eric Reiman,the Alzheimer's Disease Neuroimaging Initiative
Issue Date:June 2013
pp. 1328-1342
Structure learning of Bayesian Networks (BNs) is an important topic in machine learning. Driven by modern applications in genetics and brain sciences, accurate and efficient learning of large-scale BN structures from high-dimensional data becomes a challen...
 
The Receiver Operational Characteristic for Binary Classification with Multiple Indices and Its Application to the Neuroimaging Study of Alzheimer's Disease
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
By Xia Wu, Juan Li,Napatkamon Ayutyanont,Hillary Protas,William Jagust,Adam Fleisher,Eric Reiman, Li Yao, Kewei Chen
Issue Date:January 2013
pp. 173-180
Given a single index, the receiver operational characteristic (ROC) curve analysis is routinely utilized for characterizing performances in distinguishing two conditions/groups in terms of sensitivity and specificity. Given the availability of multiple dat...
 
Machine Learning Approaches for the Neuroimaging Study of Alzheimer's Disease
Found in: Computer
By Jieping Ye,Teresa Wu, Jing Li, Kewei Chen
Issue Date:April 2011
pp. 99-101
Machine learning tools aid many Alzheimer's disease-related investigations by enabling multisource data fusion and biomarker identification as well as analysis of functional brain connectivity.
 
The Receiver Operational Characteristic for Binary Classification with Multiple Indices and Its Application to the Neuroimaging Study of Alzheimer's Disease
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
By Adam Fleisher, Eric Reiman, Hillary Protas, Juan Li, Kewei Chen, Li Yao, Napatkamon Ayutyanont, William Jagust, Xia Wu
Issue Date:January 2013
pp. 173-180
Given a single index, the receiver operational characteristic (ROC) curve analysis is routinely utilized for characterizing performances in distinguishing two conditions/groups in terms of sensitivity and specificity. Given the availability of multiple dat...
     
Mining brain region connectivity for alzheimer's disease study via sparse inverse covariance estimation
Found in: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '09)
By Eric Reiman, Jieping Ye, Jing Li, Jun Liu, Kewei Chen, Liang Sun, Rinkal Patel, Teresa Wu
Issue Date:June 2009
pp. 1-24
Effective diagnosis of Alzheimer's disease (AD), the most common type of dementia in elderly patients, is of primary importance in biomedical research. Recent studies have demonstrated that AD is closely related to the structure change of the brain network...
     
Heterogeneous data fusion for alzheimer's disease study
Found in: Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '08)
By Eric Reiman, Gene Alexander, Huan Liu, Jieping Ye, Jing Li, Kewei Chen, Min Bae, Ravi Janardan, Rinkal Patel, Teresa Wu, Zheng Zhao
Issue Date:August 2008
pp. 5-6
Effective diagnosis of Alzheimer's disease (AD) is of primary importance in biomedical research. Recent studies have demonstrated that neuroimaging parameters are sensitive and consistent measures of AD. In addition, genetic and demographic information hav...
     
 1