activity
20202026
most citedEvaluating Large Language Models on a Highly-specialized Topic, Radiation Oncology Physics

149 citations · 188 across the 11 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

physics.med-ph2023★ 2 cited

Artificial Intelligence-Facilitated Online Adaptive Proton Therapy Using Pencil Beam Scanning Proton Therapy

Hongying Feng, Jie Shan, Carlos E. Vargas +10

We propose an oAPT workflow that incorporates all these functionalities and validate its clinical implementation feasibility with prostate patients. AI-based auto-segmentation tool…

physics.med-ph2023

Benchmarking a foundation LLM on its ability to re-label structure names in accordance with the AAPM TG-263 report

Jason Holmes, Lian Zhang, Yuzhen Ding +7

Purpose: To introduce the concept of using large language models (LLMs) to re-label structure names in accordance with the American Association of Physicists in Medicine (AAPM) Tas…

physics.med-ph2023

Artificial General Intelligence for Radiation Oncology

Chenbin Liu, Zhengliang Liu, Jason Holmes +14

The emergence of artificial general intelligence (AGI) is transforming radiation oncology. As prominent vanguards of AGI, large language models (LLMs) such as GPT-4 and PaLM 2 can…

cs.CV2023★ 24 cited

Deep-Learning-based Fast and Accurate 3D CT Deformable Image Registration in Lung Cancer

Yuzhen Ding, Hongying Feng, Yunze Yang +9

Purpose: In some proton therapy facilities, patient alignment relies on two 2D orthogonal kV images, taken at fixed, oblique angles, as no 3D on-the-bed imaging is available. The v…

physics.med-ph2023★ 149 cited

Evaluating Large Language Models on a Highly-specialized Topic, Radiation Oncology Physics

Jason Holmes, Zhengliang Liu, Lian Zhang +8

We present the first study to investigate Large Language Models (LLMs) in answering radiation oncology physics questions. Because popular exams like AP Physics, LSAT, and GRE have…