dr.ir. W. d'Hollosy (Wendy)

Assistant Professor

About Me

Wendy works in the field of health informatics, with as main topics data science, personalized eHealth technologies, clinical decision supports systems, and the application of interoperability and machine learning to optimize the referral and treatment of patients in healthcare.

She was involved at RRD (www.rrd.nl) as researcher in the H2020 Back-UP project (http://backup-project.eu/), which aims to create a predictive model to support effective and efficient treatment of neck and lower back pain. She also led the Pioneers in HealthCare (PIHC) PReferral project on the optimization of existing care pathways and referrals of patients with chronic musculoskeletal pain in 1st, 2nd and 3rd care based on artificial intelligence. Currently, she is involved in the RE-SAMPLE project that aims to develop AI-powered care for patients with COPD and other chronic illnesses (https://www.re-sample.eu/)

Wendy works 1 day a week at the University of Twente in the Biomedical Signals and System (BSS) group (https://www.utwente.nl/en/eemcs/bss) in the personalized eHealth team and 4 days a week as internal auditor at Univé (www.unive.nl), a cooperative nonprofit insurance company in the Netherlands.


Medicine & Life Sciences
Delivery Of Health Care
Low Back Pain
Machine Learning
Musculoskeletal Pain
Primary Health Care
Referral And Consultation
Engineering & Materials Science
Machine Learning


Slatman, E. S., Mossink, A., Jansen, D. J., Broeks, J., van der Lugt, P., Prosman, G.-J. , & d'Hollosy, W. (2022). Factors used by general practitioners for referring patients with chronic musculoskeletal pain: A qualitative study. BMC family practice, 23, Article 126. https://doi.org/10.1186/s12875-022-01743-6
d'Hollosy, W., Bekmann, A., Jansen, D. J., & Prosman, G.-J. (2021). The usage of patient-reported data in machine learning to predict pain rehabilitation: possible or not?. Abstract from BritSpine2021.
d'Hollosy, W., Jansen, D. J. , & Poel, M. (2021). Appropriate healthcare referrals of patients with chronic musculoskeletal pain? We can do better: a multimodal artificial intelligence approach. Abstract from 8th Dutch Bio-Medical Engineering Conference, BME 2021, Virtual Conference.
d'Hollosy, W. , Konijnendijk, A., Bessembinder, R., Leeferink, F., & Broeks, J. (2021). Towards optimized personalized referral advice and patient satisfaction in chronic musculoskeletal pain. Abstract from 8th Dutch Bio-Medical Engineering Conference, BME 2021, Virtual Conference.
Oude Nijeweme - d'Hollosy, W. , van Velsen, L. , Poel, M. , Groothuis-Oudshoorn, C., Soer, R., Stegeman, P. , & Hermens, H. (2020). Applying machine learning on patient-reported data to model the selection of appropriate treatments for low back pain: A Pilot Study. In F. Cabitza, A. Fred, & H. Gamboa (Eds.), Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) (Vol. 5: HEALTHINF, pp. 117-124). SCITEPRESS. https://doi.org/10.5220/0008962101170124
Oude Nijeweme - d'Hollosy, W., Schrijver, L. K. , & Vollenbroek-Hutten, M. M. R. (2019). E-Supporter: Personalized Technology Supported Coaching of Patients with Chronic Diseases. Poster session presented at 7th Dutch Bio-Medical Engineering Conference, BME 2019, Egmond aan zee, Netherlands.

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Courses Academic Year  2023/2024

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.

Courses Academic Year  2022/2023

Contact Details

Visiting Address

University of Twente
Drienerlolaan 5
7522 NB Enschede
The Netherlands

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Mailing Address

University of Twente
P.O. Box 217
7500 AE Enschede
The Netherlands