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Published on in Vol 28 (2026)

This is a member publication of University of Duisburg-Essen

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/82997, first published .
Improving Retrieval Augmented Generation for Health Care by Fine-Tuning Clinical Embedding Models: Development and Evaluation Study

Improving Retrieval Augmented Generation for Health Care by Fine-Tuning Clinical Embedding Models: Development and Evaluation Study

Improving Retrieval Augmented Generation for Health Care by Fine-Tuning Clinical Embedding Models: Development and Evaluation Study

Kamyar Arzideh   1, 2 , MSc ;   Henning Schäfer   1, 3 , PhD ;   Ahmad Idrissi-Yaghir   1, 4 , MSc ;   Cynthia Sabrina Schmidt   1, 3, 5 , MD ;   Bahadir Eryilmaz   1 , MSc ;   Mikel Bahn   1 , MSc ;   Amin T Turki   1, 6 , MD, PhD ;   Olivia Barbara Pollok   4 , MD ;   Eva Maria Hartmann   1, 2 , MSc ;   Philipp Winnekens   2 , MSc ;   Katarzyna Borys   1, 4 , MSc ;   Johannes Haubold   1, 4 , Prof Dr Med ;   Felix Nensa   1, 4 , Prof Dr Med ;   René Hosch   1, 4 , PhD

1 Institute for Artificial Intelligence in Medicine,, University Hospital Essen, Essen, Germany

2 Central IT Department, Data Integration Center, University Hospital Essen, Essen, Germany

3 Institute for Transfusion Medicine, University Hospital Essen, Essen, Germany

4 Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany

5 Center of Sleep and Telemedicine, University Hospital Essen, Ruhrlandklinik, Essen, Germany

6 Department of Hematology and Oncology, Ruhr-University Bochum, Marienhospital University Hospital, Bochum, Germany

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