2 citations · 5 across the 8 of their papers we have counts for
6 papers · 1 filter
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…
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…
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…
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…
Explainable AI for Fair Sepsis Mortality Predictive Model
Chia-Hsuan Chang, Xiaoyang Wang, Christopher C. Yang
Artificial intelligence supports healthcare professionals with predictive modeling, greatly transforming clinical decision-making. This study addresses the crucial need for fairnes…
An ExplainableFair Framework for Prediction of Substance Use Disorder Treatment Completion
Mary M. Lucas, Xiaoyang Wang, Chia-Hsuan Chang +3
Fairness of machine learning models in healthcare has drawn increasing attention from clinicians, researchers, and even at the highest level of government. On the other hand, the i…