Stable clinical risk prediction against distribution shift in electronic health records

S Lee, C Yin, P Zhang - Patterns, 2023 - cell.com
The availability of large-scale electronic health record datasets has led to the development
of artificial intelligence (AI) methods for clinical risk prediction that help improve patient care …

Mining Stable Preferences: Adaptive Modality Decorrelation for Multimedia Recommendation

J Zhang, Q Liu, S Wu, L Wang - … of the 46th International ACM SIGIR …, 2023 - dl.acm.org
Multimedia content is of predominance in the modern Web era. Many recommender models
have been proposed to investigate how users interact with items which are represented in …

Deep stable multi-interest learning for out-of-distribution sequential recommendation

Q Liu, Z Liu, Z Zhu, S Wu, L Wang - arxiv preprint arxiv:2304.05615, 2023 - arxiv.org
Recently, multi-interest models, which extract interests of a user as multiple representation
vectors, have shown promising performances for sequential recommendation. However …

Fairness without Demographics through Learning Graph of Gradients

Y Luo, Z Li, Q Liu, J Zhu - arxiv preprint arxiv:2412.03706, 2024 - arxiv.org
Machine learning systems are notoriously prone to biased predictions about certain
demographic groups, leading to algorithmic fairness issues. Due to privacy concerns and …

Multi-Cause Learning for Diagnosis Prediction

L Wang, Q Liu, H Ma, S Wu, L Wang - … Conference on Data Mining and Big …, 2022 - Springer
Abstract Recently, Electronic Health Records (EHR) have become valuable for enhancing
diagnosis prediction. Despite the effectiveness of existing deep learning based methods …