Toward cognitive pipelines of medical assistance algorithms
Assistance algorithms for medical tasks have great potential to support physicians with their daily work. However, medicine is also one of the most demanding domains for computer-based support systems, since medical assistance tasks are complex and the practical experience of the physician is crucia...
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| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
2016
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| In: |
OncoTarget
Year: 2015, Volume: 11, Issue: 9, Pages: 1743-1753 |
| ISSN: | 1949-2553 |
| DOI: | 10.1007/s11548-015-1322-y |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1007/s11548-015-1322-y Verlag, lizenzpflichtig, Volltext: https://link.springer.com/article/10.1007%2Fs11548-015-1322-y 
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| Author Notes: | Patrick Philipp · Maria Maleshkova · Darko Katic · Christian Weber · Michael Götz · Achim Rettinger · Stefanie Speidel · Benedikt Kämpgen · Marco Nolden · Anna-Laura Wekerle · Rüdiger Dillmann · Hannes Kenngott · Beat Müller · Rudi Studer |
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| 520 | |a Assistance algorithms for medical tasks have great potential to support physicians with their daily work. However, medicine is also one of the most demanding domains for computer-based support systems, since medical assistance tasks are complex and the practical experience of the physician is crucial. Recent developments in the area of cognitive computing appear to be well suited to tackle medicine as an application domain. | ||
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