Research Output per year
Personal profile
Research profile
Caro Fuchs graduated in 2017 at the Eindhoven University of Technology on the topic of datamining techniques applied to healthcare cases. Currently, she pursues a Ph.D. at the School of Industrial Engineering and Innovation Sciences in the Information Systems group. Her research interests include linguistically conditioned modelling, intelligent decision support systems, data analysis, machine learning and computational modelling methods. She mainly applies her research in the healthcare domain.
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Membership functions
Engineering & Materials Science
Fuzzy inference
Engineering & Materials Science
Fuzzy clustering
Engineering & Materials Science
Fuzzy rules
Engineering & Materials Science
Self-tuning
Mathematics
Fuzzy C-means Clustering
Mathematics
Fuzzy Modeling
Mathematics
Swarm Intelligence
Mathematics
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 2018 2019
A novel multi-objective approach to fuzzy clustering
Spolaor, S., Fuchs, C., Kaymak, U. & Nobile, M. S., 2019, (Accepted/In press) 2019 IEEE Symposium Series on Computational Intelligence.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Fuzzy clustering
Multiobjective optimization
Global optimization
Sorting
Clustering algorithms
A swarm intelligence approach to avoid local optima in fuzzy c-means clustering
Fuchs, C., Spolaor, S., Nobile, M. & Kaymak, U., 1 Jun 2019, 2019 IEEE International Conference on Fuzzy Systems, FUZZ 2019. Piscataway: Institute of Electrical and Electronics Engineers, 6 p. 8858940Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Self-tuning
Fuzzy C-means Clustering
Swarm Intelligence
Particle swarm optimization (PSO)
Partitioning
No age thresholds in the emergency department: a retrospective cohort study on age differences
Fuchs, C., Çelik, B., Brouns, S. H. A., Kaymak, U. & Haak, H. R., 30 Jan 2019, In : PLoS ONE. 14, 1, 11 p., e0210743.Research output: Contribution to journal › Article › Academic › peer-review
Open Access
File
Bins
cohort studies
Hospital Emergency Service
Cohort Studies
Retrospective Studies
The understanding of the quantifiers 'many' and 'most'
Fuchs, C., Vlooswijk, E., Kaymak, U. & Wilbik, A., 28 Jan 2019, Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018. Sundaram, S. (ed.). Piscataway: Institute of Electrical and Electronics Engineers, p. 189-195 7 p. 8628821Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Membership functions
Quantifiers
Linguistics
Railroad cars
Students
Towards a better understanding of the linguistic quantifiers `many' and `most'
Fuchs, C., Vlooswijk, E. A. G., Wilbik, A. & Kaymak, U., 2019.Research output: Contribution to conference › Paper › Academic
Courses
Student theses
Predicting outcomes of bariatric surgery using datamining techniques
Author: Fuchs, C., 31 Mar 2017Supervisor: Wilbik, A. (Supervisor 1), Kaymak, U. (Supervisor 2), Kusters, R. (Supervisor 2), Boer, A. (Supervisor 2) & van Loon, S. (Supervisor 2)
Student thesis: Master
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