1 citations · 1 across the 10 of their papers we have counts for
11 papers
MedCache: Efficient and Temporally Valid Memory for Longitudinal Clinical Agents
Hei Ting Chan, Hei Ting, Chan +6
Longitudinal clinical agents must maintain an evolving patient state from evidence distributed across visits, time points, and specialties. However, how agent memory should be desi…
A Cloud-Edge System for Multimodal Clinical Screening in Resource-Constrained Rural Settings
Hei Ting, Hei Ting Chan, Chan +9
Medical AI has demonstrated specialist-level diagnostic accuracy, yet these capabilities remain largely inaccessible in resource-constrained rural settings where bandwidth is scarc…
TIER-MoE: Trust-Informed Expert Routing via Conditional Modality Risk for Multimodal Fusion in Biomedical Classification
Yu Chang, Anzhe Cheng, Chenwei Wu +7
The promise of multimodal fusion lies in combining complementary sources of evidence, yet more evidence does not always yield a better prediction. Recent multimodal models have adv…
Evaluating and Understanding Model Editing for Medical Vision Language Models
Guli Zhu, Chenwei Wu, Liyue Shen
Model editing promises a fast, targeted way to correct post-deployment mistakes in medical vision-language models (VLMs) without costly retraining. However, existing multimodal mod…
Beyond Time Series: Spatial Reasoning for Epidemic Forecasting via Multimodal Learning
Diana Guadalupe Gomez, Chenwei Wu, Zhiyi Wang +2
Epidemic forecasting models typically rely on surveillance data reported over administrative regions, treating them as atomic units, thereby obscuring sub-regional spatial structur…
MedAction: Towards Active Multi-turn Clinical Diagnostic LLMs
Hsin-Ling Hsu, Zizheng Wang, Donghua Zhang +9
Most existing LLM diagnoses are evaluated on static, single-turn settings where complete patient information is provided upfront, an oversimplification of real clinical practice. W…
REMIND: Rethinking Medical High-Modality Learning under Missingness--A Long-Tailed Distribution Perspective
Chenwei Wu, Zitao Shuai, Liyue Shen
Medical multi-modal learning is critical for integrating information from a large set of diverse modalities. However, when leveraging a high number of modalities in real clinical a…
Latent Space Disentanglement in Diffusion Transformers Enables Precise Zero-shot Semantic Editing
Zitao Shuai, Chenwei Wu, Zhengxu Tang +2
Diffusion Transformers (DiTs) have recently achieved remarkable success in text-guided image generation. In image editing, DiTs project text and image inputs to a joint latent spac…
Latent Space Disentanglement in Diffusion Transformers Enables Zero-shot Fine-grained Semantic Editing
Zitao Shuai, Chenwei Wu, Zhengxu Tang +2
Diffusion Transformers (DiTs) have achieved remarkable success in diverse and high-quality text-to-image(T2I) generation. However, how text and image latents individually and joint…
Efficient In-Context Medical Segmentation with Meta-driven Visual Prompt Selection
Chenwei Wu, David Restrepo, Zitao Shuai +2
In-context learning (ICL) with Large Vision Models (LVMs) presents a promising avenue in medical image segmentation by reducing the reliance on extensive labeling. However, the ICL…
Distributionally Robust Alignment for Medical Federated Vision-Language Pre-training Under Data Heterogeneity
Zitao Shuai, Chenwei Wu, Zhengxu Tang +1
Vision-language pre-training (VLP) has emerged as an effective scheme for multimodal representation learning, but its reliance on large-scale multimodal data poses significant chal…