Keywords: Machine Learning/Artificial Intelligence, Aging, Ex-Viov Applications, Neuro (Microbleeds)Detection of cerebral microbleeds (CMBs) on ex-vivo gradient echo MR images is an important task in MRI-pathology studies in older adults. The goal of this study was to develop a confidence-aware ex-vivo CMB detection algorithm that outputs interpretable probabilities and ranking of CMB candidates on brain MRI scans of community-based older adults. The present study demonstrates that training an ex-vivo CMB detection model with confidence-aware deep learning, a technique for improving confidence estimation and ordinal ranking of examples in classification models, improves detection performance and prediction interpretability.
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