output
20062025
most citedEnhancing Clinical Concept Extraction with Contextual Embeddings

338 citations

Showing 2023 · cs.LGShow all

6 papers · 2 filters

cs.LG2023★ 1 cited

FERI: A Multitask-based Fairness Achieving Algorithm with Applications to Fair Organ Transplantation

Can Li, Dejian Lai, Xiaoqian Jiang +1

Liver transplantation often faces fairness challenges across subgroups defined by sensitive attributes such as age group, gender, and race/ethnicity. Machine learning models for ou…

cs.LG2023★ 20 cited

Self-explainable Graph Neural Network for Alzheimer's Disease And Related Dementias Risk Prediction

Xinyue Hu, Zenan Sun, Yi Nian +6

Background: Alzheimer's disease and related dementias (ADRD) ranks as the sixth leading cause of death in the US, underlining the importance of accurate ADRD risk prediction. While…

cs.LG2023★ 6 cited

Split Learning for Distributed Collaborative Training of Deep Learning Models in Health Informatics

Zhuohang Li, Chao Yan, Xinmeng Zhang +4

Deep learning continues to rapidly evolve and is now demonstrating remarkable potential for numerous medical prediction tasks. However, realizing deep learning models that generali…

cs.LG2023★ 25 cited

A Transformer-Based Deep Learning Approach for Fairly Predicting Post-Liver Transplant Risk Factors

Can Li, Xiaoqian Jiang, Kai Zhang

Liver transplantation is a life-saving procedure for patients with end-stage liver disease. There are two main challenges in liver transplant: finding the best matching patient for…

cs.LG2023★ 8 cited

Multi-Task Learning for Post-transplant Cause of Death Analysis: A Case Study on Liver Transplant

Sirui Ding, Qiaoyu Tan, Chia-yuan Chang +5

Organ transplant is the essential treatment method for some end-stage diseases, such as liver failure. Analyzing the post-transplant cause of death (CoD) after organ transplant pro…

cs.LG2023★ 3 cited

Towards Fair Patient-Trial Matching via Patient-Criterion Level Fairness Constraint

Chia-Yuan Chang, Jiayi Yuan, Sirui Ding +5

Clinical trials are indispensable in developing new treatments, but they face obstacles in patient recruitment and retention, hindering the enrollment of necessary participants. To…