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Displaying 1-8 out of 8 total
Graph Kernel-Based Learning for Gene Function Prediction from Gene Interaction Network
Found in: Bioinformatics and Biomedicine, IEEE International Conference on
By Xin Li, Zhu Zhang, Hsinchun Chen, Jiexun Li
Issue Date:November 2007
pp. 368-373
Prediction of gene functions is a major challenge to biol- ogists in the post-genomic era. Interactions between genes and their products compose networks and can be used to infer gene functions. Most previous studies used heuris- tic approaches based on ei...
 
Hospital Admission Prediction Using Pre-hospital Variables
Found in: Bioinformatics and Biomedicine, IEEE International Conference on
By Jiexun Li, Lifan Guo, Neal Handly
Issue Date:November 2009
pp. 283-286
With the rapid outstripping of healthcare resourcesby the demands on hospital care, it is important to findmore effective and efficient ways for managing care.This research is aimed at developing new admissionprediction models using various pre-hospital va...
 
Visualizing the Intellectual Structure with Paper-Reference Matrices
Found in: IEEE Transactions on Visualization and Computer Graphics
By Jian Zhang, Chaomei Chen, Jiexun Li
Issue Date:November 2009
pp. 1153-1160
Visualizing the intellectual structure of scientific domains using co-cited units such as references or authors has become a routine for domain analysis. In previous studies, paper-reference matrices are usually transformed into reference-reference matrice...
 
Genescene: Biomedical Text And Data Mining
Found in: Digital Libraries, Joint Conference on
By Gondy Leroy, Hsinchun Chen, Jesse D. Martinez, Shauna Eggers, Ryan R. Falsey, Kerri L. Kislin, Zan Huang, Jiexun Li, Jie Xu, Daniel M. McDonald, Gavin Ng
Issue Date:May 2003
pp. 116
To access the content of digital texts efficiently, it is necessary to provide more sophisticated access than keyword based searching. Genescene provides biomedical researchers with research findings and background relations automatically extracted from te...
 
Genescene: Biomedical Text And Data Mining
Found in: Digital Libraries, Joint Conference on
By Gondy Leroy, Hsinchun Chen, Jesse D. Martinez, Shauna Eggers, Ryan R. Falsey, Kerri L. Kislin, Zan Huang, Jiexun Li, Jie Xu, Daniel M. McDonald, Gavin Ng
Issue Date:May 2003
pp. 116
To access the content of digital texts efficiently, it is necessary to provide more sophisticated access than keyword based searching. Genescene provides biomedical researchers with research findings and background relations automatically extracted from te...
 
Genescene: Biomedical Text And Data Mining
Found in: Digital Libraries, Joint Conference on
By Gondy Leroy, Hsinchun Chen, Jesse D. Martinez, Shauna Eggers, Ryan R. Falsey, Kerri L. Kislin, Zan Huang, Jiexun Li, Jie Xu, Daniel M. McDonald, Gavin Ng
Issue Date:May 2003
pp. 116
To access the content of digital texts efficiently, it is necessary to provide more sophisticated access than keyword based searching. Genescene provides biomedical researchers with research findings and background relations automatically extracted from te...
 
Mining Knowledge Sharing Processes in Online Discussion Forums
Found in: 2014 47th Hawaii International Conference on System Sciences (HICSS)
By G. Alan Wang,Harry Jiannan Wang,Jiexun Li,Weiguo Fan
Issue Date:January 2014
pp. 3898-3907
Online discussion forums have become a popular knowledge source for sharing information or solving problems. This study is an attempt to apply business process modeling and mining techniques to analyzing online knowledge sharing activities. Traditional pro...
   
Automatic patent classification using citation network information: an experimental study in nanotechnology
Found in: Proceedings of the 2007 conference on Digital libraries (JCDL '07)
By Hsinchun Chen, Jiexun Li, Xin Li, Zhu Zhang
Issue Date:June 2007
pp. 419-427
Classifying and organizing documents in repositories is an active research topic in digital library studies. Manually classifying the large volume of patents and patent applications managed by patent offices is a labor-intensive task. Many previous studies...
     
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