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20242026
most citedMedPlan: A Two-Stage RAG-Based System for Personalized Medical Plan Generation

2 citations · 2 across the 12 of their papers we have counts for

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6 papers · 1 filter

cs.LG2026

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…

cs.LG2026

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…

cs.LG2026

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…

cs.LG2026

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…

cs.LG2026

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…

cs.LG2024

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…