23 citations · 81 across the 9 of their papers we have counts for
9 papers
A Comprehensive Review of Multimodal Large Language Models: Performance and Challenges Across Different Tasks
Jiaqi Wang, Hanqi Jiang, Yiheng Liu +21
In an era defined by the explosive growth of data and rapid technological advancements, Multimodal Large Language Models (MLLMs) stand at the forefront of artificial intelligence (…
Potential of Multimodal Large Language Models for Data Mining of Medical Images and Free-text Reports
Yutong Zhang, Yi Pan, Tianyang Zhong +11
Medical images and radiology reports are crucial for diagnosing medical conditions, highlighting the importance of quantitative analysis for clinical decision-making. However, the…
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…
ChatRadio-Valuer: A Chat Large Language Model for Generalizable Radiology Report Generation Based on Multi-institution and Multi-system Data
Tianyang Zhong, Wei Zhao, Yutong Zhang +39
Radiology report generation, as a key step in medical image analysis, is critical to the quantitative analysis of clinically informed decision-making levels. However, complex and d…
Instruction-ViT: Multi-Modal Prompts for Instruction Learning in ViT
Zhenxiang Xiao, Yuzhong Chen, Lu Zhang +14
Prompts have been proven to play a crucial role in large language models, and in recent years, vision models have also been using prompts to improve scalability for multiple downst…