{"id":"W4313554955","doi":"10.1109/tmi.2023.3234450","title":"Proportionally Fair Hospital Collaborations in Federated Learning of Histopathology Images","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; University of Waterloo","funders":"Mayo Clinic","keywords":"Federated learning; Computer science; Artificial intelligence; Function (biology); Scheme (mathematics); Machine learning; Data sharing; Health care; Data modeling; Database; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01506049,0.0008212032,0.001798927,0.0008512906,0.001497957,0.001932508,0.003320837,0.00190754,0.001208478],"category_scores_gemma":[0.02140132,0.0005060688,0.0007846966,0.0009597446,0.001769553,0.004477217,0.004346421,0.001710734,0.000309827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001879551,"about_ca_system_score_gemma":0.003091938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002960203,"about_ca_topic_score_gemma":0.0030575,"domain_scores_codex":[0.9939122,0.002913023,0.0002177476,0.001397701,0.0008141521,0.0007451725],"domain_scores_gemma":[0.9889842,0.005350357,0.001134799,0.002577827,0.001114094,0.0008387977],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009642307,0.0004207375,0.005416734,0.00005770941,0.00009096203,0.0001918539,0.0003336097,0.8529071,0.002317989,0.01304314,0.001857624,0.1223984],"study_design_scores_gemma":[0.00003505185,0.00009139214,0.0003034589,0.000005493667,0.00001176763,0.00004747551,0.00004968113,0.9815164,0.001418542,0.01616902,0.0003402518,0.00001152948],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1177034,0.0002490852,0.8789026,0.0006439684,0.00004880682,0.0001544787,0.00008964133,0.000987445,0.001220547],"genre_scores_gemma":[0.938414,0.00004690787,0.06006396,0.0002090021,0.00003087238,0.00008997276,0.00008299024,0.00003672436,0.001025535],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01506049,"threshold_uncertainty_score":0.07964844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01508106752166137,"score_gpt":0.2775704834577507,"score_spread":0.2624894159360893,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}