{"id":"W3016852577","doi":"10.1109/cvprw50498.2020.00502","title":"Representation Learning of Histopathology Images using Graph Neural Networks","year":2020,"lang":"en","type":"preprint","venue":"","topic":"AI in cancer detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Pooling; Computer science; Histopathology; Artificial intelligence; Pattern recognition (psychology); Graph; Lung cancer; Convolutional neural network; Adenocarcinoma; Representation (politics); Digital pathology; Pathology; Cancer; Medicine; Theoretical computer science","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":[0.0007179651,0.001253721,0.0007698862,0.002164687,0.000373923,0.001159705,0.001611385,0.00124888,0.00132369],"category_scores_gemma":[0.002696631,0.0006023337,0.001360484,0.0016346,0.0006620457,0.001739045,0.0009894902,0.001514621,0.0007251108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001740261,"about_ca_system_score_gemma":0.000816202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01503019,"about_ca_topic_score_gemma":0.0175059,"domain_scores_codex":[0.9994661,0.00009705937,0.00002182084,0.000223083,0.0001113837,0.00008055972],"domain_scores_gemma":[0.9990239,0.0003651284,0.0001483933,0.0002090016,0.0002094448,0.00004410992],"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":[0.0001430247,0.0002016775,0.004306224,0.0001496154,0.0001764336,0.0001687687,0.0001285952,0.4836754,0.01893662,0.007156635,0.008706394,0.4762506],"study_design_scores_gemma":[0.000004287936,0.00002121492,0.0005009087,0.000006040654,0.00001264897,0.0000231249,0.0000136307,0.9906088,0.002158944,0.006150072,0.0004939892,0.000006386003],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08212289,0.0006848644,0.9077482,0.0007631888,0.0000720824,0.0001102062,0.0009079311,0.005550688,0.002039949],"genre_scores_gemma":[0.7435575,0.0006722963,0.2452267,0.0004364215,0.0001403988,0.0001745775,0.004410978,0.0002640442,0.005116995],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01503019,"threshold_uncertainty_score":0.02988535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0504350833821926,"score_gpt":0.3078492448998076,"score_spread":0.257414161517615,"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."}}