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» Relevance Vector Machine Analysis of Functional Neuroimages
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BMCBI
2011
14 years 1 months ago
Conotoxin Protein Classification Using Free Scores of Words and Support Vector Machines
Background: Conotoxin has been proven to be effective in drug design and could be used to treat various disorders such as schizophrenia, neuromuscular disorders and chronic pain. ...
Nazar Zaki, Stefan Wolfsheimer, Grégory Nue...
SDM
2004
SIAM
211views Data Mining» more  SDM 2004»
14 years 11 months ago
Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects
Databases are a key technology for molecular biology which is a very data intensive discipline. Since molecular biological databases are rather heterogeneous, unification and data...
Hans-Peter Kriegel, Peer Kröger, Alexey Pryak...
MICCAI
2005
Springer
15 years 10 months ago
Exploiting Temporal Information in Functional Magnetic Resonance Imaging Brain Data
Functional Magnetic Resonance Imaging(fMRI) has enabled scientists to look into the active human brain, leading to a flood of new data, thus encouraging the development of new data...
Lei Zhang 0002, Dimitris Samaras, Dardo Tomasi, Ne...
ECIR
2003
Springer
14 years 11 months ago
A Hybrid Relevance-Feedback Approach to Text Retrieval
Abstract. Relevance feedback (RF) has been an effective query modification approach to improving the performance of information retrieval (IR) by interactively asking a user whet...
Zhao Xu, Xiaowei Xu, Kai Yu, Volker Tresp
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TREC
2004
14 years 11 months ago
Identifying Relevant Full-Text Articles for GO Annotation Without MeSH Terms
Gene Ontology (GO) is a controlled vocabulary. Given a gene product, GO enables scientists to clearly and unambiguously describe specific molecular functions of the gene product, ...
Chih Lee, Wen-Juan Hou, Hsin-Hsi Chen