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20232026
most citedTrustLLM: Trustworthiness in Large Language Models

54 citations · 258 across the 40 of their papers we have counts for

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physics.med-ph2026

Causal machine learning reveals age-dependent radiation dose effects on mandibular osteoradionecrosis

Jingyuan Chen, Yunze Yang, Olivia M. Muller +8

Distinguishing causal relationships from statistical correlations remains a fundamental challenge in clinical research, limiting the translation of observational findings into inte…

physics.med-ph2025

Causal Machine Learning Analysis of Empirical Relative Biological Effectiveness (RBE) for Mandible Osteoradionecrosis in Head and Neck Cancer Radiotherapy

Jingyuan Chen, Zhong Liu, Yunze Yang +8

Mandible Osteoradionecrosis (ORN) is one of the most severe adverse events (AEs) for head and neck (H&N) cancer radiotherapy. Previous retrospective investigations on real-world da…

physics.med-ph2024★ 9 cited

A recent evaluation on the performance of LLMs on radiation oncology physics using questions of randomly shuffled options

Peilong Wang, Jason Holmes, Zhengliang Liu +4

Purpose: We present an updated study evaluating the performance of large language models (LLMs) in answering radiation oncology physics questions, focusing on the recently released…

physics.med-ph2024

Enabling Clinical Use of Linear Energy Transfer in Proton Therapy for Head and Neck Cancer -- A Review of Implications for Treatment Planning and Adverse Events Study

Jingyuan Chen, Yunze Yang, Hongying Feng +12

Proton therapy offers significant advantages due to its unique physical and biological properties, particularly the Bragg peak, enabling precise dose delivery to tumors while spari…

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…