Personalization in biomedical-informatics: Methodological considerations and recommendations

被引:3
|
作者
Kaptein, Maurits [1 ,2 ]
机构
[1] Jheronimus Acad Data Sci, Sint Janssingel 92, NL-5211 DA Shertogenbosch, Netherlands
[2] Tilburg Univ, Stat & Res Methods, Sint Janssingel 92, NL-5211 DA Shertogenbosch, Netherlands
关键词
Personalization; Health information systems; Research methods; Sequential experimentation; Personal health records; DOUBLY ROBUST ESTIMATION; FRAMEWORK; INFERENCE; MODEL;
D O I
10.1016/j.jbi.2018.12.002
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Over the last decades there has been an increasing interest in personalization: can we make sure that treatments are effective for individual patients? The quest for personalization affects biomedical informatics in two ways: first, we design systems-for example eHealth applications-that directly interact with patients and these systems might themselves one day be personalized. Hence, we seek effective methods to do so. Second, we design systems that collect the data which will one day be used to personalize treatments: hence, we need to critically consider design requirements that improve the utility of (e.g.,) personal health records for future treatment personalization. By clearly defining personalization and analyzing the effectiveness of different personalization methods this discussion highlights how we should embrace sequential experimentation-as opposed to the traditional randomized trial-if we want to personalize our informatics systems efficiently. Furthermore, we need to make sure that we capture the treatment assignment process in our health records: doing so will greatly increase the utility of the collected data for future personalization attempts.
引用
收藏
页数:7
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