1 citations · 2 across the 8 of their papers we have counts for
8 papers
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…
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…
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…
Learning to Complement and to Defer to Multiple Users
Zheng Zhang, Wenjie Ai, Kevin Wells +3
With the development of Human-AI Collaboration in Classification (HAI-CC), integrating users and AI predictions becomes challenging due to the complex decision-making process. This…
Learning to Complement with Multiple Humans
Zheng Zhang, Cuong Nguyen, Kevin Wells +2
Real-world image classification tasks tend to be complex, where expert labellers are sometimes unsure about the classes present in the images, leading to the issue of learning with…