Abstract
The increase in available ICT infrastructure in hospitals offers cost reduction opportunities by optimizing various workflows, while maintaining quality of care. In this demonstrator-paper, we present a self-learning dashboard, for monitoring and learning the cause of delays of hospital transports. By identifying these causes, future delays in transport time can be reduced.
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References
Androutsopoulos, I., et al.: Generating natural language descriptions from owl ontologies: the naturalowl system. J. Artif. Intell. Res. 48, 671–715 (2013)
Bonte, P., Ongenae, F., Hoogstoel, E., De Turck, F.: Mining semantic rules for optimizing transport assignments in hospitals, pp. 1–6 (2016)
Bonte, P., Ongenae, F., De Turck, F.: Learning semantic rules for intelligent transport scheduling in hospitals. In: Know@LOD (2016)
Lehmann, J.: Dl-learner: learning concepts in description logics. J. Mach. Learn. Res. 10, 2639–2642 (2009)
Ongenae, F., Bonte, P., Schaballie, J., Vankeirsbilck, B., De Turck, F.: Semantic context consolidation and rule learning for optimized transport assignments in hospitals. In: Sack, H., Rizzo, G., Steinmetz, N., Mladenić, D., Auer, S., Lange, C. (eds.) ESWC 2016. LNCS, vol. 9989, pp. 88–92. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-47602-5_19
Hastreiter, S., et al.: Benchmarking logistics services in German hospitals: a research status quo. In: ICSSSM, pp. 803–808 (2013)
Vancroonenburg, W., Esprit, E., Smet, P., Vanden Berghe, G.: Optimizing internal logistic flows in hospitals by dynamic pick-up and delivery models. In: Proceedings of the 11th International Conference on the Practice and Theory of Automated Timetabling (2016)
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This research was partly funded by the AORTA project, co-funded by the AIO, imec, Xperthis, Televic Healthcare, AZMM and ZNA.
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Bonte, P., Ongenae, F., Schaballie, J., Vancroonenburg, W., Vankeirsbilck, B., De Turck, F. (2017). Context-Aware and Self-learning Dynamic Transport Scheduling in Hospitals. In: Blomqvist, E., Hose, K., Paulheim, H., Ławrynowicz, A., Ciravegna, F., Hartig, O. (eds) The Semantic Web: ESWC 2017 Satellite Events. ESWC 2017. Lecture Notes in Computer Science(), vol 10577. Springer, Cham. https://doi.org/10.1007/978-3-319-70407-4_31
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DOI: https://doi.org/10.1007/978-3-319-70407-4_31
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