BloodyWell

The BloodyWell dataset contains 3139 anonymized images of blood samples in wells where an agglutination reaction had a potential to occur. Each image is supplied with a true label based on patient's medical history, as well as an assessment from six medicinal experts on how certain they are that the agglutination is present: certainly no agglutination (0), likely no agglutination (1), uncertain (2), likely agglutination present (3), certainly agglutination present (4). File "experts_info.json" contains data annotations, where "gt_result" is a true label, "expert_votes_positions" list contains expert annotations, and other field provide additional information. The data is split in proportions of 1:4 for training and testing machine learning models respectively, stored in files "train_dataset_10_10_80.json" and "test_dataset_10_10_80.json" respectively.