9 citations · 27 across the 10 of their papers we have counts for
10 papers
TumorChain: Interleaved Multimodal Chain-of-Thought Reasoning for Traceable Clinical Tumor Analysis
Sijing Li, Zhongwei Qiu, Jiang Liu +22
Accurate tumor analysis is central to clinical radiology and precision oncology, where early detection, reliable lesion characterization, and pathology-level risk assessment guide…
Shifting Adaptation from Weight Space to Memory Space: A Memory-Augmented Agent for Medical Image Segmentation
Bowen Chen, Qiaohui Gao, Shaowen Wan +6
Medical image segmentation is fundamental to clinical workflows, yet models trained on a single dataset often fail to generalize across institutions, scanners, or patient populatio…
Fine-Tuning Open-Source Large Language Models to Improve Their Performance on Radiation Oncology Tasks: A Feasibility Study to Investigate Their Potential Clinical Applications in Radiation Oncology
Peilong Wang, Zhengliang Liu, Yiwei Li +12
Background: The radiation oncology clinical practice involves many steps relying on the dynamic interplay of abundant text data. Large language models have displayed remarkable cap…
Evaluating The Performance of Using Large Language Models to Automate Summarization of CT Simulation Orders in Radiation Oncology
Meiyun Cao, Shaw Hu, Jason Sharp +10
Purpose: This study aims to use a large language model (LLM) to automate the generation of summaries from the CT simulation orders and evaluate its performance. Materials and Metho…
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…
Towards Next-Generation Medical Agent: How o1 is Reshaping Decision-Making in Medical Scenarios
Shaochen Xu, Yifan Zhou, Zhengliang Liu +19
Artificial Intelligence (AI) has become essential in modern healthcare, with large language models (LLMs) offering promising advances in clinical decision-making. Traditional model…
HELENE: Hessian Layer-wise Clipping and Gradient Annealing for Accelerating Fine-tuning LLM with Zeroth-order Optimization
Huaqin Zhao, Jiaxi Li, Yi Pan +7
Fine-tuning large language models (LLMs) poses significant memory challenges, as the back-propagation process demands extensive resources, especially with growing model sizes. Rece…
Evaluating Large Language Models in Ophthalmology
Jason Holmes, Shuyuan Ye, Yiwei Li +11
Purpose: The performance of three different large language models (LLMS) (GPT-3.5, GPT-4, and PaLM2) in answering ophthalmology professional questions was evaluated and compared wi…
Evaluating multiple large language models in pediatric ophthalmology
Jason Holmes, Rui Peng, Yiwei Li +10
IMPORTANCE The response effectiveness of different large language models (LLMs) and various individuals, including medical students, graduate students, and practicing physicians, i…
Evaluating the Potential of Leading Large Language Models in Reasoning Biology Questions
Xinyu Gong, Jason Holmes, Yiwei Li +11
Recent advances in Large Language Models (LLMs) have presented new opportunities for integrating Artificial General Intelligence (AGI) into biological research and education. This…