collaborators

6 papers

stat.AP2026

Fracture Risk Prediction in Adults Over 50 Years Old Using DXA and EHR: Comparison of Traditional and Machine Learning Models in Two Large Cohorts

Jiahe Qian, Hao Dai, Kunyu Yu +6

Accurate fracture risk prediction is important for osteoporosis management, but commonly used clinical tools may not fully use information available in electronic health records (E…

cs.AI2026

Towards end-to-end LLM-based censoring-aware survival analysis

Yishu Wei, Hexin Dong, Yi Lin +3

Objective: Survival analysis is central to medical prediction, yet large language models (LLMs) are rarely used as end-to-end survival models because censoring prevents straightfor…

cs.CV2026

Trustworthy and Fair SkinGPT-R1 for Democratizing Dermatological Reasoning across Diverse Ethnicities

Yuhao Shen, Zhangtianyi Chen, Yuanhao He +14

The clinical translation of dermatological AI is hindered by opaque reasoning and systematic performance disparities across skin tones. Here we present SkinGPT-R1, a multimodal lar…

cs.CV2026

Towards Trustworthy Dermatology MLLMs: A Benchmark and Multimodal Evaluator for Diagnostic Narratives

Yuhao Shen, Jiahe Qian, Shuping Zhang +3

Multimodal large language models (LLMs) are increasingly used to generate dermatology diagnostic narratives directly from images. However, reliable evaluation remains the primary b…

cs.CV2025

CoTBox-TTT: Grounding Medical VQA with Visual Chain-of-Thought Boxes During Test-time Training

Jiahe Qian, Yuhao Shen, Zhangtianyi Chen +2

Medical visual question answering could support clinical decision making, yet current systems often fail under domain shift and produce answers that are weakly grounded in image ev…

cs.AI2025

Enhancing Health Fact-Checking with LLM-Generated Synthetic Data

Jingze Zhang, Jiahe Qian, Yiliang Zhou +1

Fact-checking for health-related content is challenging due to the limited availability of annotated training data. In this study, we propose a synthetic data generation pipeline t…