6 papers
People-Centred Medical Image Analysis via Fairness-Aware Human-AI Cooperation
Zheng Zhang, Milad Masroor, Cuong Nguyen +6
Machine learning models for medical image analysis often exhibit subgroup-dependent performance, which impacts how decisions should be allocated between automated systems and human…
Fairness Beyond Demographics: Optimizing Performance Across Appearance-Based Hidden Cohorts in Medical Imaging
Milad Masroor, Cuong Nguyen, Kevin Wells +1
Medical image analysis models can exhibit performance disparities across patient subgroups, threatening clinical safety and fairness. Existing methods typically address this issue…
Multi-agent decision making: A Blackwell's informativeness approach
Zheng Zhang, Cuong C. Nguyen, Kevin Wells +1
The rapid development of large language models (LLMs) has motivated research on decision-making in multi-agent systems, where multiple agents collaborate to achieve shared objectiv…
Fatigue-Aware Learning to Defer via Constrained Optimisation
Zheng Zhang, Cuong C. Nguyen, David Rosewarne +2
Learning to defer (L2D) enables human-AI cooperation by deciding when an AI system should act autonomously or defer to a human expert. Existing L2D methods, however, assume static…
Coverage-Constrained Human-AI Cooperation with Multiple Experts
Zheng Zhang, Cuong Nguyen, Kevin Wells +3
Human-AI cooperative classification (HAI-CC) approaches aim to develop hybrid intelligent systems that enhance decision-making in various high-stakes real-world scenarios by levera…
Fair Distillation: Teaching Fairness from Biased Teachers in Medical Imaging
Milad Masroor, Tahir Hassan, Yu Tian +4
Deep learning has achieved remarkable success in image classification and segmentation tasks. However, fairness concerns persist, as models often exhibit biases that disproportiona…