most citedAugGPT: Leveraging ChatGPT for Text Data Augmentation

99 citations · 187 across the 13 of their papers we have counts for

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cs.CL20236 cited

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…

cs.CL20234 cited

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…

cs.CL202312 cited

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…

cs.CL202315 cited

CohortGPT: An Enhanced GPT for Participant Recruitment in Clinical Study

Zihan Guan, Zihao Wu, Zhengliang Liu +5

Participant recruitment based on unstructured medical texts such as clinical notes and radiology reports has been a challenging yet important task for the cohort establishment in c…

cs.CL20231 cited

Coupling Artificial Neurons in BERT and Biological Neurons in the Human Brain

Xu Liu, Mengyue Zhou, Gaosheng Shi +6

Linking computational natural language processing (NLP) models and neural responses to language in the human brain on the one hand facilitates the effort towards disentangling the…

cs.CL202399 cited

AugGPT: Leveraging ChatGPT for Text Data Augmentation

Haixing Dai, Zhengliang Liu, Wenxiong Liao +15

Text data augmentation is an effective strategy for overcoming the challenge of limited sample sizes in many natural language processing (NLP) tasks. This challenge is especially p…