7 papers
Automated Clinical Problem Detection from SOAP Notes using a Collaborative Multi-Agent LLM Architecture
Yeawon Lee, Xiaoyang Wang, Christopher C. Yang
Accurate interpretation of clinical narratives is critical for patient care, but the complexity of these notes makes automation challenging. While Large Language Models (LLMs) show…
MoE-Health: A Mixture of Experts Framework for Robust Multimodal Healthcare Prediction
Xiaoyang Wang, Christopher C. Yang
Healthcare systems generate diverse multimodal data, including Electronic Health Records (EHR), clinical notes, and medical images. Effectively leveraging this data for clinical pr…
DeepSelective: Interpretable Prognosis Prediction via Feature Selection and Compression in EHR Data
Ruochi Zhang, Qian Yang, Xiaoyang Wang +10
The rapid accumulation of Electronic Health Records (EHRs) has transformed healthcare by providing valuable data that enhance clinical predictions and diagnoses. While conventional…
Balancing Fairness and Performance in Healthcare AI: A Gradient Reconciliation Approach
Xiaoyang Wang, Christopher C. Yang
The rapid growth of healthcare data and advances in computational power have accelerated the adoption of artificial intelligence (AI) in medicine. However, AI systems deployed with…
Enhancing Multi-Attribute Fairness in Healthcare Predictive Modeling
Xiaoyang Wang, Christopher C. Yang
Artificial intelligence (AI) systems in healthcare have demonstrated remarkable potential to improve patient outcomes. However, if not designed with fairness in mind, they also car…
FakeBench: Probing Explainable Fake Image Detection via Large Multimodal Models
Yixuan Li, Xuelin Liu, Xiaoyang Wang +4
The ability to distinguish whether an image is generated by artificial intelligence (AI) is a crucial ingredient in human intelligence, usually accompanied by a complex and dialect…