Personal profile
Subject classification (UKÄ)
- Cancer and Oncology
- Radiology and Medical Imaging
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 3 Good Health and Well-being
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Collaborations the last five years
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Deep learning on routine full-breast mammograms enhances lymph node metastasis prediction in early breast cancer
Zhang, D., Dihge, L., Bendahl, P.-O., Arvidsson, I., Dustler, M., Ellbrant, J., Gulis, K., Hjärtström, M., Ohlsson, M., Rejmer, C., Schmidt, D., Zackrisson, S., Edén, P. & Rydén, L., 2025 Jul 10, In: npj Digital Medicine. 8, 1, 425.Research output: Contribution to journal › Article › peer-review
Open Access -
Enhancing the Prediction of Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Routine Full-Breast Mammograms
Zhang, D., Dihge, L., Bendahl, P.-O., Arvidsson, I., Dustler, M., Ellbrant, J., Gulis, K., Hjärtström, M., Ohlsson, M., Rejmer, C., Schmidt, D., Zackrisson, S., Edén, P. & Ryden, L., 2025 Jan 6, (Submitted) Research Square, (Breast Cancer Research).Research output: Working paper/Preprint › Preprint (in preprint archive)
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Prediction of sentinel lymph node status in patients with early breast cancer using breast imaging as an alternative to surgical staging-a systematic review and meta-analysis
Rejmer, C., Hjärtström, M., Bendahl, P.-O., Dihge, L., Skarping, I., Zhang, D., Dustler, M. & Rydén, L., 2025, In: Systematic Reviews. 14, 1, 246.Research output: Contribution to journal › Article › peer-review
Open Access -
Preoperative prediction of nodal status using clinical data and artificial intelligence derived mammogram features enabling abstention of sentinel lymph node biopsy in breast cancer
Rejmer, C., Dihge, L., Bendahl, P.-O., Förnvik, D., Dustler, M. & Rydén, L., 2024, In: Frontiers in Oncology. 14, 1394448.Research output: Contribution to journal › Article › peer-review
Open Access -
Prediction of node negative breast cancer and high disease burden through image analysis software on mammographic images and clinicopathological data
Rejmer, C., Dihge, L., Bendahl, P.-O., Förnvik, D., Dustler, M. & Ryden, L., 2022, In: Cancer Research. 82, 4, Suppl, P1-01-09.Research output: Contribution to journal › Published meeting abstract
Open Access
Projects
- 1 Active
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Clinical prediction models for lymph node staging using mammographic imaging software programs and clinicopathological data
Rejmer, C. (Research student), Ryden, L. (Supervisor), Dihge, L. (Assistant supervisor), Dustler, M. (Assistant supervisor) & Bendahl, P.-O. (Assistant supervisor)
2022/02/01 → …
Project: Dissertation