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200P Leveraging large language models for identifying CyberKnife radiotherapy in oligometastatic breast cancer: A time-saving tool for retrospective studies
0
Zitationen
4
Autoren
2025
Jahr
Abstract
Large Language Models (LLMs) have the potential to streamline retrospective oncology research by extracting structured insights from free-text clinical reports. At the Centre Antoine Lacassagne (CAL), in Nice, we explored their use for identifying breast cancer patients who received CyberKnife radiotherapy to cerebral metastases in an oligometastatic context, where precise manual selection is time-consuming and resource-intensive.
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