Blind study for the prediction of attendance to a UK breast cancer screening unit

Author

Arochena, Hisbel E. ; Naguib, Raouf N G ; Todman, Alison G. ; Wheaton, Margot E. ; Wallis, Matthew G.

Author_Institution

Sch. of Math. & Inf. Sci., Coventry Univ., UK

fYear

2003

fDate

24-26 April 2003

Firstpage

219

Lastpage

221

Abstract

This paper presents a blind study carried out in the Solihull, Coventry and Warwickshire Breast Cancer Screening Unit in the UK, aiming to evaluate the performance of the Artificial Intelligence Attendance algorithm (AI-ATT), in predicting attendance of women to screening invitations. Achieving a 76% accuracy on the blind data, it is concluded that this algorithm is a useful predictive tool, not only for the prediction of attendance of individuals, but also for the identification of possible non-attendees.

Keywords

artificial intelligence; cancer; mammography; medical diagnostic computing; Artificial Intelligence Attendance algorithm; Coventry; Solihull; UK; UK breast cancer screening unit; Warwickshire Breast Cancer Screening Unit; attendance prediction; blind data; possible nonattendees identification; screening invitations; Aging; Artificial intelligence; Breast cancer; Databases; History; Hospitals; Logistics; Prediction algorithms; Predictive models; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Technology Applications in Biomedicine, 2003. 4th International IEEE EMBS Special Topic Conference on

Print_ISBN

0-7803-7667-6

Type

conf

DOI

10.1109/ITAB.2003.1222515

Filename

1222515