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.
Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.
research interest
Social Sciences
Fuzzy inference
Engineering & Materials Science
Fuzzy rules
Engineering & Materials Science
Membership functions
Engineering & Materials Science
information system
Social Sciences
data analysis
Social Sciences
marketing
Social Sciences
engineering
Social Sciences
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 2018 2019
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., e0210743Research 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 (IEEE), 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
An enhanced approach to rule base simplification of first-order takagi-sugeno fuzzy inference systems
Fuchs, C. E. M., Wilbik, A. M., van Loon, S. L. M., Boer, A-K. & Kaymak, U., 2018, Advances in Fuzzy Logic and Technology 2017: Proceedings of: EUSFLAT- 2017 – The 10th Conference of the European Society for Fuzzy Logic and Technology, September 11-15, 2017, Warsaw, Poland IWIFSGN’2017 – The Sixteenth International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, September 13-15, 2017, Warsaw, Poland, Volume 2. Kacprzyk, J., Szmidt, E., Zadrożny, S., Atanassov, K. T. & Krawczak, M. (eds.). Dordrecht: Springer, p. 92-103 12 p. (Advances in Intelligent Systems and Computing; vol. 642)Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Fuzzy inference
Fuzzy rules
Membership functions
On the interaction between feature selection and parameter determination in fuzzy modelling
Chen, P., Fuchs, C., Wilbik, A., Chan, T. M., van Loon, S., Boer, A. K., Lu, X., Scharnhorst, V. & Kaymak, U., 1 Jan 2018, Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications - 17th International Conference, IPMU 2018, Proceedings: 17th International Conference, IPMU 2018, Cádiz, Spain, June 11-15, 2018, Proceedings, Part III. Medina, J., Perfilieva, I. & Yager, R. R. (eds.). Dordrecht: Springer, p. 150-161 12 p. (Communications in Computer and Information Science; vol. 855)Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Fuzzy Modeling
Feature Selection
Feature extraction
Interaction
Model
Towards more specific estimation of membership functions for data-driven fuzzy inference systems
Fuchs, C. E. M., Wilbik, A. M. & Kaymak, U., Jul 2018, 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) . Piscataway: Institute of Electrical and Electronics Engineers (IEEE), 8 p. 8491524Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Fuzzy inference
Membership functions
Fuzzy clustering
Fuzzy rules
Identification (control systems)
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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