Towards a New Science of a Clinical Data Intelligence
Towards a New Science of a Clinical Data Intelligence
In this paper we define Clinical Data Intelligence as the analysis of data generated in the clinical routine with the goal of improving patient care. We define a science of a Clinical Data Intelligence as a data analysis that permits the derivation of scientific, i.e., generalizable and reliable results. We argue that a science of a Clinical Data Intelligence is sensible in the context of a Big Data analysis, i.e., with data from many patients and with complete patient information. We discuss that Clinical Data Intelligence requires the joint efforts of knowledge engineering, information extraction (from textual and other unstructured data), and statistics and statistical machine learning. We describe some of our main results as conjectures and relate them to a recently funded research project involving two major German university hospitals.
Sonja Zillner、Maria J. Costa、Daniel Sonntag、Thomas Wittenberg、Denis Krompass、Thomas Ganslandt、Klemens Budde、Volker Tresp、Yi Huang、Philipp Daumke、Patricia G. Oppelt、Alexander Cavallaro、Danilo Schmidt、Andre Reis、Carl Hinrichs、Peter A. Fasching、Martin Sedlmayr
医学研究方法临床医学生物科学研究方法、生物科学研究技术
Sonja Zillner,Maria J. Costa,Daniel Sonntag,Thomas Wittenberg,Denis Krompass,Thomas Ganslandt,Klemens Budde,Volker Tresp,Yi Huang,Philipp Daumke,Patricia G. Oppelt,Alexander Cavallaro,Danilo Schmidt,Andre Reis,Carl Hinrichs,Peter A. Fasching,Martin Sedlmayr.Towards a New Science of a Clinical Data Intelligence[EB/OL].(2013-11-17)[2025-06-16].https://arxiv.org/abs/1311.4180.点此复制
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