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Support vector machine / Lung cancer staging / TNM staging system / Learning classifier system / Multiclass classification / Classifier / Binary classification / Boosting methods for object categorization / Statistics / Statistical classification / Machine learning


Multi-class Classification of Cancer Stages from Free-text Histology Reports using Support Vector Machines Anthony Nguyen, Darren Moore, Iain McCowan and Mary-Jane Courage Abstract— Multi-class machine learning techniq
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Document Date: 2011-12-13 17:39:46


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City

Brisbane / Brighton / Windsor / Sydney / /

Company

AUSLAB Support Group / Multiple Classifier Systems / Knowledge-Based Intelligent Engineering Systems / Neural Networks / MIT Press / Analysis Team / Allied Technologies / Queensland Cancer Control / /

Country

Australia / United Kingdom / New Zealand / /

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Event

Product Recall / Business Partnership / Product Issues / /

Facility

CSIRO eHealth Research Centre / /

IndustryTerm

cancer staging tool / lung cancer staging protocol / classification systems / multi-class classification systems / text pre-processing steps / multi-class systems / /

MedicalCondition

cancer / tumour / lung cancer / metastatic cancer / Automated cancer / different cancer / /

Organization

Thoracic Society of Australia / Cancer Council Australia / CSIRO eHealth Research Centre / MIT / /

Person

Steven Armstrong / Iain McCowan / Shoni Colquist / Darren Moore / Jaccalyne Brady / Christopher M. Bishop / Donna Fry / Mary-Jane Courage Abstract / Wayne Watson / Rayleen Bowman / Belinda Clarke / Vector Machines Anthony Nguyen / Max Norm / Hazel Harden / /

Position

Governor / /

Product

CLASS CLASSIFIER / /

ProvinceOrState

Texas / Queensland / /

PublishedMedium

Machine Learning / Journal of Machine Learning Research / /

Technology

SVM algorithms / staging protocol / machine learning / TNM lung cancer staging protocol / decision support system / /

URL

http /

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