Multiple Instance Learning (MIL) is a paradigm within machine learning that addresses the challenge of weakly supervised data, where complete labels for individual instances are not available but are ...

The proposed framework leverages weakly supervised multiple-instance learning (MIL) to reduce false-positive predictions. A novel morphology-based slide aggregation method is introduced to improve ...