most citedTowards Personalized Federated Learning via Heterogeneous Model Reassembly

13 citations · 18 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2024

Automated Multi-Task Learning for Joint Disease Prediction on Electronic Health Records

Suhan Cui, Prasenjit Mitra

In the realm of big data and digital healthcare, Electronic Health Records (EHR) have become a rich source of information with the potential to improve patient care and medical res…

cs.LG2024★ 1 cited

Automated Fusion of Multimodal Electronic Health Records for Better Medical Predictions

Suhan Cui, Jiaqi Wang, Yuan Zhong +3

The widespread adoption of Electronic Health Record (EHR) systems in healthcare institutes has generated vast amounts of medical data, offering significant opportunities for improv…

cs.AI2023★ 2 cited

Hierarchical Pretraining on Multimodal Electronic Health Records

Xiaochen Wang, Junyu Luo, Jiaqi Wang +5

Pretraining has proven to be a powerful technique in natural language processing (NLP), exhibiting remarkable success in various NLP downstream tasks. However, in the medical domai…

cs.LG2023★ 2 cited

MedDiffusion: Boosting Health Risk Prediction via Diffusion-based Data Augmentation

Yuan Zhong, Suhan Cui, Jiaqi Wang +7

Health risk prediction is one of the fundamental tasks under predictive modeling in the medical domain, which aims to forecast the potential health risks that patients may face in…

cs.LG2023★ 13 cited

Towards Personalized Federated Learning via Heterogeneous Model Reassembly

Jiaqi Wang, Xingyi Yang, Suhan Cui +4

This paper focuses on addressing the practical yet challenging problem of model heterogeneity in federated learning, where clients possess models with different network structures.…