collaborators

5 papers

eess.IV2025

Attention-Guided Fair AI Modeling for Skin Cancer Diagnosis

Mingcheng Zhu, Mingxuan Liu, Han Yuan +4

Artificial intelligence (AI) has shown remarkable promise in dermatology, offering accurate and non-invasive diagnosis of skin cancer. While extensive research has addressed skin t…

cs.LG2025

Equitable Survival Prediction: A Fairness-Aware Survival Modeling (FASM) Approach

Mingxuan Liu, Yilin Ning, Haoyuan Wang +5

As machine learning models become increasingly integrated into healthcare, structural inequities and social biases embedded in clinical data can be perpetuated or even amplified by…

cs.CL2025

Gender Bias in Large Language Models for Healthcare: Assignment Consistency and Clinical Implications

Mingxuan Liu, Yuhe Ke, Wentao Zhu +9

The integration of large language models (LLMs) into healthcare holds promise to enhance clinical decision-making, yet their susceptibility to biases remains a critical concern. Ge…

eess.SP2025

Deep Survival Analysis from Adult and Pediatric Electrocardiograms: A Multi-center Benchmark Study

Platon Lukyanenko, Joshua Mayourian, Mingxuan Liu +3

Artificial intelligence applied to electrocardiography (AI-ECG) shows potential for mortality prediction, but heterogeneous approaches and private datasets have limited generalizab…

cs.LG2025

seeBias: A Comprehensive Tool for Assessing and Visualizing AI Fairness

Yilin Ning, Yian Ma, Mingxuan Liu +2

Fairness in artificial intelligence (AI) prediction models is increasingly emphasized to support responsible adoption in high-stakes domains such as health care and criminal justic…