5 citations · 11 across the 12 of their papers we have counts for
5 papers · 1 filter
Label Critic: Design Data Before Models
Pedro R. A. S. Bassi, Qilong Wu, Wenxuan Li +4
As medical datasets rapidly expand, creating detailed annotations of different body structures becomes increasingly expensive and time-consuming. We consider that requesting radiol…
Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang +50
How can we test AI performance? This question seems trivial, but it isn't. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified…
A Hybrid Federated Kernel Regularized Least Squares Algorithm
Celeste Damiani, Yulia Rodina, Sergio Decherchi
Federated learning is becoming an increasingly viable and accepted strategy for building machine learning models in critical privacy-preserving scenarios such as clinical settings.…
Training with Explanations Alone: A New Paradigm to Prevent Shortcut Learning
Pedro R. A. S. Bassi, Haydr A. H. Ali, Andrea Cavalli +1
Application of Artificial Intelligence (AI) in critical domains, like the medical one, is often hampered by shortcut learning, which hinders AI generalization to diverse hospitals…
Faster ISNet for Background Bias Mitigation on Deep Neural Networks
Pedro R. A. S. Bassi, Sergio Decherchi, Andrea Cavalli
Bias or spurious correlations in image backgrounds can impact neural networks, causing shortcut learning (Clever Hans Effect) and hampering generalization to real-world data. ISNet…