Stratifying Cervical Cancer Risk With Registry Data

被引：1

作者：

Baltzer, Nicholas ^{[1
]}

Sundstrom, Karin ^{[2
]}

Nygard, Jan ^{[3
]}

Nygard, Mari ^{[3
]}

Dillner, Joakim ^{[2
]}

Komorowski, Jan ^{[1
,4
]}

机构：

[1] Uppsala Univ, Dept Cell & Mol Biol, Uppsala, Sweden

[2] Karolinska Inst, Dept Lab Med, Stockholm, Sweden

[3] Canc Registry Norway, Dept Registry Informat, Oslo, Norway

[4] Polish Acad Sci, Warsaw, Poland

来源：

2018 IEEE 14TH INTERNATIONAL CONFERENCE ON E-SCIENCE (E-SCIENCE 2018) | 2018年

关键词：

cancer; bioinformatics; algorithms; precision medicine; medical analytics; prediction; classification;

D O I：

10.1109/eScience.2018.00055

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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.

引用

页码：288 / 289

页数：2

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