Research The basis for continuous improvement

The scientific work carried out by the Teaching, Research and Development department supports the clinic’s departments and thus helps improve patient care. Our research work is continuously providing new insights into the treatment of orthopaedic patients and reinforcing Schulthess Klinik’s international reputation as a centre of excellence.

Schulthess Klinik

Schulthess Klinik
Lengghalde 2
8008 Zürich
Switzerland

Teaching, Research and Development

Read more about Current research projects

Current research projects

Find out more about current research projects at Schulthess Klinik below. The projects are financed by the Wilhelm Schulthess Foundation’s Research Fund. With your donation, you can specifically support one of the projects or our research work in general. The latest scientific findings directly benefit our patients and many others around the world. 

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Publications

This is where you will find a list of the most important publications in peer-reviewed journals by Schulthess Klinik staff.
For further literature research, we recommend the online database PubMed, which contains an extensive range of material from a variety of authors on different medical topics.

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Partnerships

We make a difference with top-class medical services, a humane approach and innovation, along with a strong network consisting of over 60 Swiss and international cooperation partners from practice and science.

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Our research specialists

Latest news

Read more about Research: Automatic calculation of cervical spine parameters using deep learning
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Research: Automatic calculation of cervical spine parameters using deep learning

Researchers at the Schulthess Clinic have co-authored a study that examines a model that allows for more accurate, automatic measurement of spinal parameters during X-rays. The model is based on deep learning and supports surgeons in particular in the diagnosis of adjacent segment disease.

Read more about Research: Automatic calculation of cervical spine parameters using deep learning