AUSLAB Support Group / MIT Press / Analysis Team / MEDLINE / Queensland Cancer Control / /
Country
New Zealand / Australia / / /
Event
Business Partnership / /
Facility
CSIRO eHealth Research Centre / /
IndustryTerm
soft computing / text categorisation systems / software tools / optimum decoding algorithm / dynamic programming algorithm / prognostic tool / deterministic algorithms / implemented using search / lung cancer staging protocol / automatic coding systems / natural language processing / above systems / /
MedicalCondition
inhalational anthrax / Carcinoma / Distant metastasis / each cancer / regional lymph node metastasis / cancer / disease / cervical cancer / tumour / patient’s lung cancer / fever / patient’s cancer / lung cancer / metastatic cancer / diseases / acute gastrointestinal syndrome / Tumour Nodes Metastases / different cancer / distant metastases / specific medical diseases / disorders / Primary tumor / on staging lung cancer / /
MedicalTreatment
surgery / /
Organization
Collaborative Staging Task Force / American Medical Informatics Association / Thoracic Society of Australia / CSIRO eHealth Research Centre / MIT / American Joint Committee on Cancer / Cancer Council Australia / International Union Against Cancer / Norwegian Computing Center / /
Person
Darren Moore / Jaccalyne Brady / Donna Fry / Mary-Jane Fry Abstract / Wayne Watson / Rayleen Bowman / Steven Armstrong / Shoni Colquist / Belinda Clarke / Hazel Harden / /
Position
Governor / pathologist / /
ProvinceOrState
Western Australia / Queensland / S.K. / /
PublishedMedium
Machine Learning / IEEE Transactions on Information Theory / /
Classification of Cancer Stage from Free-text Histology Reports Iain McCowan, Darren Moore, Mary-Jane Fry Abstract— This article investigates the classification of a patient’s lung cancer stage based on analysis of t