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Presenting a simplified assistant tool for breast cancer diagnosis in mammography to radiologists

By Ping Zhang, Jenny Doust and Kuldeep Kumar


This paper proposes a method to simplify a computational model from logistic regression for clinical use without computer. The model was built using human interpreted features including some BI-RADS standardized features for diagnosing the malignant masses. It was compared with the diagnosis using only assessment categorization from BI-RADS. The research aims at assisting radiologists to diagnose the malignancy of breast cancer in a way without using automated computer aided diagnosis system

Topics: breast cancer diagnosis, mammography, logistic regression, simplified model, Analytical, Diagnostic and Therapeutic Techniques and Equipment, Radiology
Publisher: ePublications@bond
Year: 2010
OAI identifier: oai:epublications.bond.edu.au:hsm_pubs-1211
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