activity
20202026
most citedOpportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health

372 citations · 1.1k across the 17 of their papers we have counts for

collaborators

19 papers

cs.CV2026

VOLMO: Versatile and Open Large Models for Ophthalmology

Zhenyue Qin, Younjoon Chung, Elijah Lee +16

Vision impairment affects millions globally, and early detection is critical to preventing irreversible vision loss. Ophthalmology workflows require clinicians to integrate medical…

cs.CV2025★ 2 cited

LMOD+: A Comprehensive Multimodal Dataset and Benchmark for Developing and Evaluating Multimodal Large Language Models in Ophthalmology

Zhenyue Qin, Yang Liu, Yu Yin +13

Vision-threatening eye diseases pose a major global health burden, with timely diagnosis limited by workforce shortages and restricted access to specialized care. While multimodal…

cs.CL2025★ 1 cited

Memorization in Large Language Models in Medicine: Prevalence, Characteristics, and Implications

Anran Li, Lingfei Qian, Mengmeng Du +18

Large Language Models (LLMs) have demonstrated significant potential in medicine, with many studies adapting them through continued pre-training or fine-tuning on medical data to e…

cs.CL2024★ 7 cited

Enhancing Large Language Models with Domain-specific Retrieval Augment Generation: A Case Study on Long-form Consumer Health Question Answering in Ophthalmology

Aidan Gilson, Xuguang Ai, Thilaka Arunachalam +19

Despite the potential of Large Language Models (LLMs) in medicine, they may generate responses lacking supporting evidence or based on hallucinated evidence. While Retrieval Augmen…

eess.IV2024★ 13 cited

AI Workflow, External Validation, and Development in Eye Disease Diagnosis

Qingyu Chen, Tiarnan D L Keenan, Elvira Agron +35

Timely disease diagnosis is challenging due to increasing disease burdens and limited clinician availability. AI shows promise in diagnosis accuracy but faces real-world applicatio…

cs.CL2023★ 2 cited

Ascle: A Python Natural Language Processing Toolkit for Medical Text Generation

Rui Yang, Qingcheng Zeng, Keen You +13

This study introduces Ascle, a pioneering natural language processing (NLP) toolkit designed for medical text generation. Ascle is tailored for biomedical researchers and healthcar…

cs.CV2023★ 60 cited

A scoping review on multimodal deep learning in biomedical images and texts

Zhaoyi Sun, Mingquan Lin, Qingqing Zhu +4

Computer-assisted diagnostic and prognostic systems of the future should be capable of simultaneously processing multimodal data. Multimodal deep learning (MDL), which involves the…

cs.IR2023★ 167 cited

MedCPT: Contrastive Pre-trained Transformers with Large-scale PubMed Search Logs for Zero-shot Biomedical Information Retrieval

Qiao Jin, Won Kim, Qingyu Chen +4

Information retrieval (IR) is essential in biomedical knowledge acquisition and clinical decision support. While recent progress has shown that language model encoders perform bett…

cs.CL2023

BioREx: Improving Biomedical Relation Extraction by Leveraging Heterogeneous Datasets

Po-Ting Lai, Chih-Hsuan Wei, Ling Luo +2

Biomedical relation extraction (RE) is the task of automatically identifying and characterizing relations between biomedical concepts from free text. RE is a central task in biomed…

cs.CY2023★ 372 cited

Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health

Shubo Tian, Qiao Jin, Lana Yeganova +11

ChatGPT has drawn considerable attention from both the general public and domain experts with its remarkable text generation capabilities. This has subsequently led to the emergenc…

cs.CL2023

Utilizing Longitudinal Chest X-Rays and Reports to Pre-Fill Radiology Reports

Qingqing Zhu, Tejas Sudharshan Mathai, Pritam Mukherjee +3

Despite the reduction in turn-around times in radiology reports with the use of speech recognition software, persistent communication errors can significantly impact the interpreta…

cs.CL2023★ 174 cited

GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical Information

Qiao Jin, Yifan Yang, Qingyu Chen +1

While large language models (LLMs) have been successfully applied to various tasks, they still face challenges with hallucinations. Augmenting LLMs with domain-specific tools such…

cs.CL2023★ 172 cited

Benchmarking large language models for biomedical natural language processing applications and recommendations

Qingyu Chen, Yan Hu, Xueqing Peng +18

The rapid growth of biomedical literature poses challenges for manual knowledge curation and synthesis. Biomedical Natural Language Processing (BioNLP) automates the process. While…

cs.CL2023★ 68 cited

Improving Large Language Models for Clinical Named Entity Recognition via Prompt Engineering

Yan Hu, Qingyu Chen, Jingcheng Du +9

Objective: This study quantifies the capabilities of GPT-3.5 and GPT-4 for clinical named entity recognition (NER) tasks and proposes task-specific prompts to improve their perform…

cs.CV2023★ 2 cited

Interpretable Medical Image Visual Question Answering via Multi-Modal Relationship Graph Learning

Xinyue Hu, Lin Gu, Kazuma Kobayashi +6

Medical visual question answering (VQA) aims to answer clinically relevant questions regarding input medical images. This technique has the potential to improve the efficiency of m…

cs.CL2023★ 16 cited

Bioformer: an efficient transformer language model for biomedical text mining

Li Fang, Qingyu Chen, Chih-Hsuan Wei +2

Pretrained language models such as Bidirectional Encoder Representations from Transformers (BERT) have achieved state-of-the-art performance in natural language processing (NLP) ta…

cs.CV2021★ 25 cited

Perceiving and Modeling Density is All You Need for Image Dehazing

Tian Ye, Mingchao Jiang, Yunchen Zhang +4

In the real world, the degradation of images taken under haze can be quite complex, where the spatial distribution of haze is varied from image to image. Recent methods adopt deep…

eess.IV2021★ 8 cited

SDWNet: A Straight Dilated Network with Wavelet Transformation for Image Deblurring

Wenbin Zou, Mingchao Jiang, Yunchen Zhang +3

Image deblurring is a classical computer vision problem that aims to recover a sharp image from a blurred image. To solve this problem, existing methods apply the Encode-Decode arc…

eess.IV2020★ 15 cited

COVID-19-CT-CXR: a freely accessible and weakly labeled chest X-ray and CT image collection on COVID-19 from biomedical literature

Yifan Peng, Yu-Xing Tang, Sungwon Lee +3

The latest threat to global health is the COVID-19 outbreak. Although there exist large datasets of chest X-rays (CXR) and computed tomography (CT) scans, few COVID-19 image collec…