12 citations · 31 across the 10 of their papers we have counts for
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eess.IV2024
Uncertainty-Error correlations in Evidential Deep Learning models for biomedical segmentation
Hai Siong Tan, Kuancheng Wang, Rafe Mcbeth
In this work, we examine the effectiveness of an uncertainty quantification framework known as Evidential Deep Learning applied in the context of biomedical image segmentation. Thi…
cs.CL2024
From Generalist to Specialist: Improving Large Language Models for Medical Physics Using ARCoT
Jace Grandinetti, Rafe McBeth
Large Language Models (LLMs) have achieved remarkable progress, yet their application in specialized fields, such as medical physics, remains challenging due to the need for domain…
cs.LG2024★ 10 cited
Deep Evidential Learning for Radiotherapy Dose Prediction
Hai Siong Tan, Kuancheng Wang, Rafe Mcbeth
In this work, we present a novel application of an uncertainty-quantification framework called Deep Evidential Learning in the domain of radiotherapy dose prediction. Using medical…