A non-invasive, automated diagnosis of Menière’s disease using radiomics and machine learning on conventional magnetic resonance imaging: A multicentric, case-controlled feasibility study
- M.F.J.A. van der Lubbe*
- , A. Vaidyanathan
- , M. de Wit
- , E.L. van den Burg
- , A.A. Postma
- , T.D. Bruintjes
- , M.A.L. Bilderbeek-Beckers
- , P.F.M. Dammeijer
- , S. Vanden Bossche
- , V. Van Rompaey
- , P. Lambin
- , M. van Hoof
- , R. van de Berg
*Corresponding author for this work
- Keel-, Neus- en Oorheelkunde
- MHeNs - Cognitive Neuropsychiatry and Clinical Neuroscience
- GROW - Basic and Translational Cancer Biology
- Precision Medicine
- Beeldvorming
- DA BV AIOS Radiologie
- DA BV Medisch Specialisten Radiologie
- GROW - Innovative Cancer Diagnostics & Therapy
- MA AIOS Keel Neus Oorheelkunde
- MA Vestibulogie
- MA Audiologisch Centrum Maastricht
- MA Keel Neus Oorheelkunde
Research output: Contribution to journal › Article › Academic › peer-review