The new year 2025 marks the beginning of a new chapter for Biomedical Engineering/Biomedizinische Technik. In cooperation with the editors, the publisher will convert the journal to Diamond Open Access in accordance with the Subscribe to Open (S2O) model, on a year-by-year basis.
Starting 2025, all articles will immediately appear under the Creative Commons license CC-BY at no publication costs for the authors. The open access transformation is based on an alternative, sustainable and equitable approach to transitioning subscription-based journals one year at a time, through the continuation of existing subscriptions. The prerequisite for successful transformation is that subscriptions are continued to the same extent as before. The editors of Biomedical Engineering/Biomedizinische Technik and the publisher De Gruyter would therefore like to thank all subscribers for their support.
Subscribe to Open was developed in 2019 by the US publisher Annual Reviews. Since then, a growing number of publishers and libraries have opted for S2O and joined forces in the Community of Practice. The publisher launched a pilot project in 2020/2021 that has proven to be a real success story. The S2O portfolio currently comprises 21 titles, with plans to transfer a further 37 journals to the S2O program by 2025 and up to 90 % of the journal portfolio by 2028.
The proportion of open access publications in the fields of biomedical engineering, health technology, medical information technology, and biotechnology has increased significantly in recent years, and in several countries and regions it has almost become the standard, not least because funders and institutions are imposing open research requirements. Above all, we are aware of the enormous social need to make rational, accurate information available to everyone and thus promoting scientific developments as best as possible.
With S2O, we aim to eliminate barriers not only at the end of the authors, who may not have the means to cover Article Processing Charges (APCs), but also for our readers. Open access increases visibility, reach, and overall impact of the published research. Initial analyses of the current S2O portfolio show that the published open access content is used up to seven times more than the articles published behind the paywall, and the number of countries from which the content is accessed has increased massively.
You can easily support the S20 model of Biomedical Engineering/Biomedizinische Technik by renewing your existing subscription in the usual way or reaching out to your librarian and recommend a subscription for 2025. Please refer to the De Gruyter website, reach out to the editorial office or contact Senior Manager Open Research Strategy Dr. Christina Lembrecht (christina.lembrecht@degruyter.com) for further information.
Further readings
We wish you a successful and happy New Year 2025!
On behalf of the Publisher and the Editorial Board of Biomedical Engineering/Biomedizinische Technik
Katharina J. Appelt (Journals Manager Medicine, De Gruyter Brill)
Jens Haueisen (Editor-in-Chief)
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: The authors have accepted responsibility for the entire content of this article and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: None declared.
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Research funding: None declared.
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Data availability: Not applicable.
© 2024 the author(s), published by De Gruyter, Berlin/Boston
This work is licensed under the Creative Commons Attribution 4.0 International License.
Articles in the same Issue
- Frontmatter
- Editorial
- Change of publication model for Biomedical Engineering/Biomedizinische Technik
- Research Articles
- Mechano-responses of quadriceps muscles evoked by transcranial magnetic stimulation
- A type-2 fuzzy inference-based approach enables walking speed estimation that adapts to inter-individual gait patterns
- DeepCOVIDNet-CXR: deep learning strategies for identifying COVID-19 on enhanced chest X-rays
- Prediction of muscular-invasive bladder cancer using multi-view fusion self-distillation model based on 3D T2-Weighted images
- Evaluation of the RF depositions at 3T in routine clinical scans with respect to the SAR safety to improve efficiency of MRI utilization
- A software tool for fabricating phantoms mimicking human tissues with designated dielectric properties and frequency
- MedShapeNet – a large-scale dataset of 3D medical shapes for computer vision
- Concept and development of a telemedical supervision system for anesthesiology in operating rooms using the interoperable communication standard ISO/IEEE 11073 SDC
Articles in the same Issue
- Frontmatter
- Editorial
- Change of publication model for Biomedical Engineering/Biomedizinische Technik
- Research Articles
- Mechano-responses of quadriceps muscles evoked by transcranial magnetic stimulation
- A type-2 fuzzy inference-based approach enables walking speed estimation that adapts to inter-individual gait patterns
- DeepCOVIDNet-CXR: deep learning strategies for identifying COVID-19 on enhanced chest X-rays
- Prediction of muscular-invasive bladder cancer using multi-view fusion self-distillation model based on 3D T2-Weighted images
- Evaluation of the RF depositions at 3T in routine clinical scans with respect to the SAR safety to improve efficiency of MRI utilization
- A software tool for fabricating phantoms mimicking human tissues with designated dielectric properties and frequency
- MedShapeNet – a large-scale dataset of 3D medical shapes for computer vision
- Concept and development of a telemedical supervision system for anesthesiology in operating rooms using the interoperable communication standard ISO/IEEE 11073 SDC