Abstract
In this paper, we describe how we combine active and passive user input modes in clinical environments for knowledge discovery and knowledge acquisition towards decision support in clinical environments. Active input modes include digital pens, smartphones, and automatic handwriting recognition for a direct digitalisation of patient data. Passive input modes include sensors of the clinical environment and or mobile smartphones. This combination for knowledge acquisition and decision support (while using machine learning techniques) has not yet been explored in clinical environments and is of specific interest because it combines previously unconnected information sources for individualised treatments. The innovative aspect is a holistic view on individual patients based on ontologies, terminologies, and textual patient records whereby individual active and passive real-time patient data can be taken into account for improving clinical decision support.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - IEEE Symposium on Computer-Based Medical Systems |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 351-356 |
| Number of pages | 6 |
| ISBN (Print) | 9781479944354 |
| DOIs | |
| Publication status | Published - 2014 |
| Event | 27th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2014 - New York, NY, United States Duration: May 27 2014 → May 29 2014 |
Other
| Other | 27th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2014 |
|---|---|
| Country | United States |
| City | New York, NY |
| Period | 5/27/14 → 5/29/14 |
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Keywords
- clinical decision support
- computer-based medical systems
- cyber-physical systems
- knowledge acquisition
ASJC Scopus subject areas
- Computer Science Applications
- Radiology Nuclear Medicine and imaging
Cite this
The medical cyber-physical systems activity at EIT : A look under the hood. / Sonntag, Daniel; Zillner, Sonja; Chakraborty, Samarjit; Lőrincz, A.; Strommer, Esko; Serafini, Luciano.
Proceedings - IEEE Symposium on Computer-Based Medical Systems. Institute of Electrical and Electronics Engineers Inc., 2014. p. 351-356 6881905.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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TY - GEN
T1 - The medical cyber-physical systems activity at EIT
T2 - A look under the hood
AU - Sonntag, Daniel
AU - Zillner, Sonja
AU - Chakraborty, Samarjit
AU - Lőrincz, A.
AU - Strommer, Esko
AU - Serafini, Luciano
PY - 2014
Y1 - 2014
N2 - In this paper, we describe how we combine active and passive user input modes in clinical environments for knowledge discovery and knowledge acquisition towards decision support in clinical environments. Active input modes include digital pens, smartphones, and automatic handwriting recognition for a direct digitalisation of patient data. Passive input modes include sensors of the clinical environment and or mobile smartphones. This combination for knowledge acquisition and decision support (while using machine learning techniques) has not yet been explored in clinical environments and is of specific interest because it combines previously unconnected information sources for individualised treatments. The innovative aspect is a holistic view on individual patients based on ontologies, terminologies, and textual patient records whereby individual active and passive real-time patient data can be taken into account for improving clinical decision support.
AB - In this paper, we describe how we combine active and passive user input modes in clinical environments for knowledge discovery and knowledge acquisition towards decision support in clinical environments. Active input modes include digital pens, smartphones, and automatic handwriting recognition for a direct digitalisation of patient data. Passive input modes include sensors of the clinical environment and or mobile smartphones. This combination for knowledge acquisition and decision support (while using machine learning techniques) has not yet been explored in clinical environments and is of specific interest because it combines previously unconnected information sources for individualised treatments. The innovative aspect is a holistic view on individual patients based on ontologies, terminologies, and textual patient records whereby individual active and passive real-time patient data can be taken into account for improving clinical decision support.
KW - clinical decision support
KW - computer-based medical systems
KW - cyber-physical systems
KW - knowledge acquisition
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U2 - 10.1109/CBMS.2014.83
DO - 10.1109/CBMS.2014.83
M3 - Conference contribution
SN - 9781479944354
SP - 351
EP - 356
BT - Proceedings - IEEE Symposium on Computer-Based Medical Systems
PB - Institute of Electrical and Electronics Engineers Inc.
ER -