collaborators

5 papers

cs.AI2026

Learning a Continuous Sepsis Severity Score Without Hour-by-Hour Supervision: A Two-Site Retrospective Study

Kevin Zhu, Ryan Zhang, Baraa Abed +18

Currently used sepsis severity indices rely on fixed variables and weights established decades ago, which are coarsely discretized and calibrated to a cohort that no longer reflect…

cs.CV2026

DA-SegFormer: Damage-Aware Semantic Segmentation for Fine-Grained Disaster Assessment

Kevin Zhu, William Tang, Raphael Hay Tene +3

Rapid and accurate damage assessment following natural disasters is critical for effective emergency response. However, identifying fine-grained damage levels (e.g., distinguishing…

cs.LG2026

Clin-JEPA: A Multi-Phase Co-Training Framework for Joint-Embedding Predictive Pretraining on EHR Patient Trajectories

Yixuan Yang, Mehak Arora, Ryan Zhang +10

We present Clin-JEPA, a multi-phase co-training framework for joint-embedding predictive (JEPA) pretraining on EHR patient trajectories. JEPA architectures have enabled latent-spac…

eess.IV2025

Adapting Large Language Models to Mitigate Skin Tone Biases in Clinical Dermatology Tasks: A Mixed-Methods Study

Kiran Nijjer, Ryan Bui, Derek Jiu +4

SkinGPT-4, a large vision-language model, leverages annotated skin disease images to augment clinical workflows in underserved communities. However, its training dataset predominan…

eess.IV2025

Evaluating the Impact of Radiographic Noise on Chest X-ray Semantic Segmentation and Disease Classification Using a Scalable Noise Injection Framework

Derek Jiu, Kiran Nijjer, Nishant Chinta +2

Deep learning models are increasingly used for radiographic analysis, but their reliability is challenged by the stochastic noise inherent in clinical imaging. A systematic, cross-…