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AI in Hand and Wrist Radiography: Multimodal Large Language Models for Distal Radius Fracture Detection and Characterization
0
Zitationen
6
Autoren
2026
Jahr
Abstract
: Only two models exceeded 90% sensitivity for fracture detection, while intra-articular extension remained at chance level (≤55.6%). Substantial inter-run reliability (κ > 0.60) was observed in only one model. These findings indicate that current MLLMs do not reliably support multidimensional fracture assessment and that single-run evaluations overestimate robustness.
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Autoren
Institutionen
- Friedrich-Alexander-Universität Erlangen-Nürnberg(DE)
- Otto-von-Guericke-Universität Magdeburg(DE)
- Gemeinschaftskrankenhaus Havelhöhe(DE)
- RWTH Aachen University(DE)
- Witten/Herdecke University(DE)
- University Hospital of Zurich(CH)
- Krankenhaus Waldfriede(DE)
- Berlin Center for Epidemiology and Health Research(DE)