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BMCBI
2005
251views more  BMCBI 2005»
13 years 9 months ago
Contextual weighting for Support Vector Machines in literature mining: an application to gene versus protein name disambiguation
Background: The ability to distinguish between genes and proteins is essential for understanding biological text. Support Vector Machines (SVMs) have been proven to be very effici...
Tapio Pahikkala, Filip Ginter, Jorma Boberg, Jouni...
BMCBI
2004
252views more  BMCBI 2004»
13 years 8 months ago
Applying Support Vector Machines for Gene ontology based gene function prediction
Background: The current progress in sequencing projects calls for rapid, reliable and accurate function assignments of gene products. A variety of methods has been designed to ann...
Arunachalam Vinayagam, Rainer König, Jutta Mo...
TMI
2010
172views more  TMI 2010»
13 years 7 months ago
Comparison of AdaBoost and Support Vector Machines for Detecting Alzheimer's Disease Through Automated Hippocampal Segmentation
Abstract— We compared four automated methods for hippocampal segmentation using different machine learning algorithms (1) hierarchical AdaBoost, (2) Support Vector Machines (SVM)...
Jonathan H. Morra, Zhuowen Tu, Liana G. Apostolova...
BMCBI
2011
13 years 4 months ago
Support vector machines-based identification of alternative splicing in Arabidopsis thaliana from whole-genome tiling arrays
Background: Alternative splicing (AS) is a process which generates several distinct mRNA isoforms from the same gene by splicing different portions out of the precursor transcript...
Johannes Eichner, Georg Zeller, Sascha Laubinger, ...
COLING
2010
13 years 4 months ago
Recognizing Medication related Entities in Hospital Discharge Summaries using Support Vector Machine
Due to the lack of annotated data sets, there are few studies on machine learning based approaches to extract named entities (NEs) in clinical text. The 2009 i2b2 NLP challenge is...
Son Doan, Hua Xu