TY  - BOOK
AU  - Kati?, Darko
AB  - To manage the influx of information into surgical practice, new man-machine interaction methods are necessary to prevent information overflow. This work presents an approach to automatically segment surgeries into phases and select the most appropriate pieces of information for the current situation. This way, assistance systems can adopt themselves to the needs of the surgeon and not the other way around.
DO  - 10.5445/KSP/1000054609
ID  - OAPEN ID: 34632
KW  - Maschinelles Lernen
KW  - Assistenz
KW  - Ontologie
KW  - Ontology
KW  - Surgery
KW  - Augmented Reality
KW  - Chirurgie
KW  - Erweiterte RealitätMachine Learning
KW  - Assistance
L1  - https://www.ksp.kit.edu/9783731505273
LA  - English
LK  - https://directory.doabooks.org/handle/20.500.12854/59441
PB  - KIT Scientific Publishing
PY  - 2016
SN  - 9783731505273
TI  - Situation Interpretation for Knowledge- and Model Based Laparoscopic Surgerynull
ER  - 
