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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.

Fingerprint Dive into the research topics where Caro E.M. Fuchs is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 4 Similar Profiles
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

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Research Output 2018 2019

  • 8 Citations
  • 7 Conference contribution
  • 1 Paper
  • 1 Article

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 proceedingConference contributionAcademicpeer-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. 8858940

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Self-tuning
Fuzzy C-means Clustering
Swarm Intelligence
Particle swarm optimization (PSO)
Partitioning
35 Downloads (Pure)

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 journalArticleAcademicpeer-review

Open Access
File
Bins
cohort studies
Hospital Emergency Service
Cohort Studies
Retrospective Studies
6 Downloads (Pure)

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. 8628821

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-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 conferencePaperAcademic

Courses

Business process simulation

1/09/13 → …

Course

Healthcare information systems

1/09/12 → …

Course

Student theses

Predicting outcomes of bariatric surgery using datamining techniques

Author: Fuchs, C., 31 Mar 2017

Supervisor: Wilbik, A. (Supervisor 1), Kaymak, U. (Supervisor 2), Kusters, R. (Supervisor 2), Boer, A. (Supervisor 2) & van Loon, S. (Supervisor 2)

Student thesis: Master

File