Stratifying Cervical Cancer Risk With Registry Data

• The cervical cancer screening programmes in Sweden and Norway have successfully reduced the frequency of cervical cancer incidence but have not implemented any form of evaluation for screening needs. This means that the screening frequency for individuals can he suboptimal, increasing either the cost of the programme or the risk of missing an early stage cancer development. We developed a framework for assessing an individual's risk of cervical cancer based on their available screening history and computing a primary risk factor called CRS from a data-driven separation model together with multiple derived attributes. The results show that this approach is highly practical, validates against multiple established trends, and can he effective in personalizing the screening needs for individuals.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Bioinformatics (hsv//eng)

Nyckelord

cancer

bioinformatics

algorithms

precision medicine

medical analytics

prediction

classification

Publikations- och innehållstyp

ref (ämneskategori)

kon (ämneskategori)