1 citations · 1 across the 16 of their papers we have counts for
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Automated stereotactic radiosurgery planning using a human-in-the-loop reasoning large language model agent
Humza Nusrat, Luke Francisco, Bing Luo +10
Stereotactic radiosurgery (SRS) demands precise dose shaping around critical structures, yet black-box AI systems have limited clinical adoption due to opacity concerns. We tested…
FluenceFormer: Transformer-Driven Multi-Beam Fluence Map Regression for Radiotherapy Planning
Ujunwa Mgboh, Rafi Ibn Sultan, Joshua Kim +2
Fluence map prediction is central to automated radiotherapy planning but remains an ill-posed inverse problem due to the complex relationship between volumetric anatomy and beam-in…
Calibrating LLM Confidence by Probing Perturbed Representation Stability
Reza Khanmohammadi, Erfan Miahi, Mehrsa Mardikoraem +5
Miscalibration in Large Language Models (LLMs) undermines their reliability, highlighting the need for accurate confidence estimation. We introduce CCPS (Calibrating LLM Confidence…
Characterization and ex vivo application of flexible 2D scintillating coatings in ultra-high dose rate electron beams for FLASH radiotherapy
Verdi Vanreusel, Stephen Brown, Shujat Ali +11
The increasing interest in FLASH-RT has lead to the conversion of linear accelerators to enable ultra-high dose rate (UHDR) beams for preclinical research. Dosimetry hereof remains…
Autonomous Radiotherapy Treatment Planning Using DOLA: A Privacy-Preserving, LLM-Based Optimization Agent
Humza Nusrat, Bing Luo, Ryan Hall +5
Radiotherapy treatment planning is a complex and time-intensive process, often impacted by inter-planner variability and subjective decision-making. To address these challenges, we…