2026-02-05 15:18 |
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2026-02-05 15:15 |
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2026-02-05 14:47 |
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2026-02-05 14:44 |
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2026-02-05 14:43 |
[DKFZ-2026-00280]
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Yang, S. ; Zhou, F. ; Mayer, L. ; et al
Large-scale self-supervised video foundation model for intelligent surgery.
Computer-Assisted Intervention has the potential to revolutionize modern surgery, with surgical scene understanding serving as a critical component in supporting decision-making and improving procedural efficacy. While existing AI-driven approaches alleviate annotation burdens via self-supervised spatial representation learning, their lack of explicit temporal modeling during pre-training fundamentally restricts the capture of dynamic surgical contexts, resulting in incomplete spatiotemporal understanding. [...]
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2026-02-05 14:41 |
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2026-02-05 14:12 |
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2026-02-04 14:38 |
[DKFZ-2026-00276]
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Kottlors, J. ; Iuga, A.-I. ; Bluethgen, C. ; et al
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Large language models (LLMs) have transformative potential in radiology, including textual summaries, diagnostic decision support, proofreading, and image analysis. However, the rapid increase in studies investigating these models, along with the lack of standardized LLM-specific reporting practices, affects reproducibility, reliability, and clinical applicability. [...]
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2026-02-04 14:35 |
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