5 papers
Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework
Zihan Guan, Rituparna Datta, Mengxuan Hu +5
Large language models (LLMs) have shown promise in constructing mechanistic models from data. However, existing evaluations largely focus on simplified settings and fail to capture…
Large Language Models Lack Temporal Awareness of Medical Knowledge
Zihan Guan, Qiao Jin, Guangzhi Xiong +6
The existing methods for evaluating the medical knowledge of Large Language Models (LLMs) are largely based on atemporal examination-style benchmarks, while in reality, medical kno…
Improving Epidemic Analyses with Privacy-Preserving Integration of Sensitive Data
Zihan Guan, Zhiyuan Zhao, Fengwei Tian +5
Epidemic analyses increasingly rely on heterogeneous datasets, many of which are sensitive and require strong privacy protection. Although differential privacy (DP) has become a st…
Agentic Framework for Epidemiological Modeling
Rituparna Datta, Zihan Guan, Baltazar Espinoza +5
Epidemic modeling is essential for public health planning, yet traditional approaches rely on fixed model classes that require manual redesign as pathogens, policies, and scenario…
Improving Hospital Risk Prediction with Knowledge-Augmented Multimodal EHR Modeling
Rituparna Datta, Jiaming Cui, Zihan Guan +5
Accurate prediction of clinical outcomes using Electronic Health Records (EHRs) is critical for early intervention, efficient resource allocation, and improved patient care. EHRs c…