25 citations · 53 across the 9 of their papers we have counts for
7 papers · 1 filter
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…
Predicting multiple sclerosis disease severity with multimodal deep neural networks
Kai Zhang, John A. Lincoln, Xiaoqian Jiang +2
Multiple Sclerosis (MS) is a chronic disease developed in human brain and spinal cord, which can cause permanent damage or deterioration of the nerves. The severity of MS disease i…
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…
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…
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…
A Fast PC Algorithm with Reversed-order Pruning and A Parallelization Strategy
Kai Zhang, Chao Tian, Kun Zhang +2
The PC algorithm is the state-of-the-art algorithm for causal structure discovery on observational data. It can be computationally expensive in the worst case due to the conditiona…