3 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.CV2025
Benchmarking GPT-5 in Radiation Oncology: Measurable Gains, but Persistent Need for Expert Oversight
Ugur Dinc, Jibak Sarkar, Philipp Schubert +16
Introduction: Large language models (LLM) have shown great potential in clinical decision support. GPT-5 is a novel LLM system that has been specifically marketed towards oncology…
cs.AI2024★ 2 cited
Fine-Tuning a Local LLaMA-3 Large Language Model for Automated Privacy-Preserving Physician Letter Generation in Radiation Oncology
Yihao Hou, Christoph Bert, Ahmed Gomaa +12
Generating physician letters is a time-consuming task in daily clinical practice. This study investigates local fine-tuning of large language models (LLMs), specifically LLaMA mode…
eess.IV2023★ 3 cited
The Segment Anything foundation model achieves favorable brain tumor autosegmentation accuracy on MRI to support radiotherapy treatment planning
Florian Putz, Johanna Grigo, Thomas Weissmann +13
Background: Tumor segmentation in MRI is crucial in radiotherapy (RT) treatment planning for brain tumor patients. Segment anything (SA), a novel promptable foundation model for au…