Brunner, Jens O.
Jens O Brunner researcher
VIAF ID: 107688257 ( Personal )
Permalink: http://viaf.org/viaf/107688257
Preferred Forms
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- 100 1 _ ‡a Brunner, Jens O.
- 100 1 _ ‡a Brunner, Jens O.
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- 100 1 _ ‡a Brunner, Jens O.
- 100 1 _ ‡a Brunner, Jens O.
- 100 1 _ ‡a Brunner, Jens O.
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- 100 0 _ ‡a Jens O Brunner ‡c researcher
4xx's: Alternate Name Forms (3)
5xx's: Related Names (7)
- 510 2 _ ‡a Danmarks Tekniske Universitet ‡4 affi ‡4 https://d-nb.info/standards/elementset/gnd#affiliation ‡e Affiliation
- 510 2 _ ‡a München, Techn. Univ
- 510 2 _ ‡a Technische Universität München ‡4 affi ‡4 https://d-nb.info/standards/elementset/gnd#affiliation ‡e Affiliation
- 510 2 _ ‡a Technische Universität München
- 510 2 _ ‡a Universität Augsburg ‡4 affi ‡4 https://d-nb.info/standards/elementset/gnd#affiliation ‡e Affiliation
- 510 2 _ ‡a Universität Augsburg ‡b Wirtschaftswissenschaftliche Fakultät ‡4 affi ‡4 https://d-nb.info/standards/elementset/gnd#affiliation ‡e Affiliation
- 510 2 _ ‡a Universität Augsburg ‡b Wirtschaftswissenschaftliche Fakultät
Works
Title | Sources |
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Analyzing the accuracy of variable returns to scale data envelopment analysis models | |
Analyzing the relative efficiency of internationalization in the university business model: the case of Germany | |
Automated classification of airborne pollen using neural networks | |
Balancing control and autonomy in master surgery scheduling: benefits of ICU quotas for recovery units | |
Covid-19 triage in the emergency department 2.0: how analytics and AI transform a human-made algorithm for the prediction of clinical pathways | |
COVIDAL: a machine learning classifier for digital COVID-19 diagnosis in German hospitals | |
Determinants of the utilization of allergy management measures among hay fever sufferers: a theory-based cross-sectional study | |
Evaluating the real exposure of allergics to airborne pollen: too high, too early, too long or too complex? [Abstract] | |
Evaluation von scorebasierten Ansätzen für die Ex-post-Triage auf Intensivstationen während der COVID-19-Pandemie: eine simulationsbasierte Analyse | |
Flexible Shift Planning in the Service Industry The Case of Physicians in Hospitals | |
Homogeneity and best practice analyses in hospital performance management: an analytical framework | |
Machine learning–supported prediction of dual variables for the cutting stock problem with an application in stabilized column generation | |
Managing admission and discharge processes in intensive care units | |
Managing hospital visitor admission during Covid-19: a discrete-event simulation by the data of a German university hospital | |
Nasal biomarker‐profiles to distinguish between high‐ and low‐symptomatic, non‐allergic and allergic subjects in a natural pollen exposure study [Abstract] | |
Pollen allergy and health behavior: patients trivializing their disease | |
Predicting intensive care unit bed occupancy for integrated operating room scheduling via neural networks | |
A scalable forecasting framework to predict COVID-19 hospital bed occupancy | |
Simulation-based evaluation of operating room management policies | |
Stable annual scheduling of medical residents using prioritized multiple training schedules to combat operational uncertainty | |
Towards automatic airborne pollen monitoring: from commercial devices to operational by mitigating class-imbalance in a deep learning approach |