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20232025
most citedColaCare: Enhancing Electronic Health Record Modeling through Large Language Model-Driven Multi-Agent Collaboration

26 citations · 82 across the 11 of their papers we have counts for

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Showing 2024Show all

9 papers · 1 filter

cs.CV2024

SuperGS: Super-Resolution 3D Gaussian Splatting Enhanced by Variational Residual Features and Uncertainty-Augmented Learning

Shiyun Xie, Zhiru Wang, Xu Wang +3

Recently, 3D Gaussian Splatting (3DGS) has exceled in novel view synthesis (NVS) with its real-time rendering capabilities and superior quality. However, it faces challenges for hi…

cs.LG2024★ 26 cited

ColaCare: Enhancing Electronic Health Record Modeling through Large Language Model-Driven Multi-Agent Collaboration

Zixiang Wang, Yinghao Zhu, Huiya Zhao +9

We introduce ColaCare, a framework that enhances Electronic Health Record (EHR) modeling through multi-agent collaboration driven by Large Language Models (LLMs). Our approach seam…

cs.CV2024★ 4 cited

SpecGaussian with Latent Features: A High-quality Modeling of the View-dependent Appearance for 3D Gaussian Splatting

Zhiru Wang, Shiyun Xie, Chengwei Pan +1

Recently, the 3D Gaussian Splatting (3D-GS) method has achieved great success in novel view synthesis, providing real-time rendering while ensuring high-quality rendering results.…

cs.CL2024★ 2 cited

ClinicRealm: Re-evaluating Large Language Models with Conventional Machine Learning for Non-Generative Clinical Prediction Tasks

Yinghao Zhu, Junyi Gao, Zixiang Wang +9

Large Language Models (LLMs) are increasingly deployed in medicine. However, their utility in non-generative clinical prediction, often presumed inferior to specialized models, rem…

cs.CL2024★ 24 cited

EMERGE: Enhancing Multimodal Electronic Health Records Predictive Modeling with Retrieval-Augmented Generation

Yinghao Zhu, Changyu Ren, Zixiang Wang +7

The integration of multimodal Electronic Health Records (EHR) data has significantly advanced clinical predictive capabilities. Existing models, which utilize clinical notes and mu…

cs.CR2024

Medical MLLM is Vulnerable: Cross-Modality Jailbreak and Mismatched Attacks on Medical Multimodal Large Language Models

Xijie Huang, Xinyuan Wang, Hantao Zhang +6

Security concerns related to Large Language Models (LLMs) have been extensively explored, yet the safety implications for Multimodal Large Language Models (MLLMs), particularly in…

cs.CV2024

AGFSync: Leveraging AI-Generated Feedback for Preference Optimization in Text-to-Image Generation

Jingkun An, Yinghao Zhu, Zongjian Li +6

Text-to-Image (T2I) diffusion models have achieved remarkable success in image generation. Despite their progress, challenges remain in both prompt-following ability, image quality…

cs.AI2024★ 11 cited

REALM: RAG-Driven Enhancement of Multimodal Electronic Health Records Analysis via Large Language Models

Yinghao Zhu, Changyu Ren, Shiyun Xie +8

The integration of multimodal Electronic Health Records (EHR) data has significantly improved clinical predictive capabilities. Leveraging clinical notes and multivariate time-seri…

cs.CL2024★ 8 cited

Prompting Large Language Models for Zero-Shot Clinical Prediction with Structured Longitudinal Electronic Health Record Data

Yinghao Zhu, Zixiang Wang, Junyi Gao +6

The inherent complexity of structured longitudinal Electronic Health Records (EHR) data poses a significant challenge when integrated with Large Language Models (LLMs), which are t…