This article is about a new project that combines clinical data intelligence and smart data. It provides an introduction to the Klinische Datenintelligenz (KDI) project which is founded by the Federal Ministry for Economic Affairs and Energy (BMWi); we transfer research and development results (R&D) of the analysis of data which are generated in the clinical routine in specific medical domain. We present the project structure and goals, how patient care should be improved, and the joint efforts of data and knowledge engineering, information extraction (from textual and other unstructured data), statistical machine learning, decision support, and their integration into special use cases moving towards individualised medicine. In particular, we describe some details of our medical use cases and cooperation with two major German university hospitals.
%0 Journal Article
%1 SonntagTrespEtAl16insk
%A Sonntag, Daniel
%A Tresp, Volker
%A Zillner, Sonja
%A Cavallaro, Alexander
%A Hammon, Matthias
%A Reis, André
%A Fasching, Peter A.
%A Sedlmayr, Martin
%A Ganslandt, Thomas
%A Prokosch, Hans-Ulrich
%A Budde, Klemens
%A Schmidt, Danilo
%A Hinrichs, Carl
%A Wittenberg, Thomas
%A Daumke, Philipp
%A Oppelt, Patricia G.
%D 2016
%J Informatik-Spektrum
%K 01801 springer paper ai knowledge information management processing data pattern analysis learn health zzz.big
%N 4
%P 290--300
%R 10.1007/s00287-015-0913-x
%T The Clinical Data Intelligence Project
%V 39
%X This article is about a new project that combines clinical data intelligence and smart data. It provides an introduction to the Klinische Datenintelligenz (KDI) project which is founded by the Federal Ministry for Economic Affairs and Energy (BMWi); we transfer research and development results (R&D) of the analysis of data which are generated in the clinical routine in specific medical domain. We present the project structure and goals, how patient care should be improved, and the joint efforts of data and knowledge engineering, information extraction (from textual and other unstructured data), statistical machine learning, decision support, and their integration into special use cases moving towards individualised medicine. In particular, we describe some details of our medical use cases and cooperation with two major German university hospitals.
@article{SonntagTrespEtAl16insk,
abstract = {This article is about a new project that combines clinical data intelligence and smart data. It provides an introduction to the Klinische Datenintelligenz (KDI) project which is founded by the Federal Ministry for Economic Affairs and Energy (BMWi); we transfer research and development results (R\&D) of the analysis of data which are generated in the clinical routine in specific medical domain. We present the project structure and goals, how patient care should be improved, and the joint efforts of data and knowledge engineering, information extraction (from textual and other unstructured data), statistical machine learning, decision support, and their integration into special use cases moving towards individualised medicine. In particular, we describe some details of our medical use cases and cooperation with two major German university hospitals.},
added-at = {2016-09-21T09:50:44.000+0200},
author = {Sonntag, Daniel and Tresp, Volker and Zillner, Sonja and Cavallaro, Alexander and Hammon, Matthias and Reis, André and Fasching, Peter A. and Sedlmayr, Martin and Ganslandt, Thomas and Prokosch, Hans-Ulrich and Budde, Klemens and Schmidt, Danilo and Hinrichs, Carl and Wittenberg, Thomas and Daumke, Philipp and Oppelt, Patricia G.},
biburl = {https://www.bibsonomy.org/bibtex/22364735d3807cd7aeee42f6079ffa694/flint63},
doi = {10.1007/s00287-015-0913-x},
file = {SpringerLink:2016/SonntagTrespEtAl16insk.pdf:PDF},
groups = {public},
interhash = {c3292f49c09e858646013d3f8305b649},
intrahash = {2364735d3807cd7aeee42f6079ffa694},
issn = {0170-6012},
journal = {Informatik-Spektrum},
keywords = {01801 springer paper ai knowledge information management processing data pattern analysis learn health zzz.big},
month = {#aug#},
number = 4,
pages = {290--300},
timestamp = {2018-04-16T12:01:42.000+0200},
title = {The {Clinical} {Data} {Intelligence} {Project}},
username = {flint63},
volume = 39,
year = 2016
}