{"id":"W3185576150","doi":"10.1109/embc46164.2021.9630818","title":"A Similarity Measure of Histopathology Images by Deep Embeddings","year":2021,"lang":"en","type":"article","venue":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","topic":"AI in cancer detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Artificial intelligence; Similarity (geometry); Pattern recognition (psychology); Pixel; Measure (data warehouse); Computer science; Similarity measure; Magnification; Pooling; Feature extraction; Embedding; Computer vision; Image (mathematics); Mathematics; Data mining","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":[0.0008509338,0.0008021203,0.000739172,0.003639061,0.0002704219,0.001376139,0.0007392175,0.0009842175,0.001819516],"category_scores_gemma":[0.004387866,0.0002117363,0.0006863663,0.001887456,0.0005481921,0.002567378,0.001520811,0.0006270168,0.0007373843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007606126,"about_ca_system_score_gemma":0.0004478317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009520379,"about_ca_topic_score_gemma":0.001206354,"domain_scores_codex":[0.9987398,0.0001472083,0.0001468955,0.0003016139,0.0005660161,0.00009850876],"domain_scores_gemma":[0.9983151,0.0003589288,0.0003737857,0.0002173148,0.0006427231,0.00009207877],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001077006,0.0003536384,0.01536567,0.0005953213,0.0003991633,0.0003655,0.0002671157,0.06457107,0.1511646,0.01280984,0.007411922,0.7456191],"study_design_scores_gemma":[0.00003577623,0.0007711638,0.02000806,0.00007398627,0.0001246795,0.001232721,0.0002319738,0.8909466,0.07112987,0.01080802,0.004549505,0.00008768986],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2244987,0.001232626,0.7687023,0.000249694,0.0001580792,0.000185514,0.0009144687,0.001299304,0.00275937],"genre_scores_gemma":[0.8012331,0.000542242,0.1930749,0.0001281792,0.0001108949,0.000137454,0.00201872,0.0001882976,0.002566103],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003639061,"threshold_uncertainty_score":0.006086886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02593490423859503,"score_gpt":0.2864590160768847,"score_spread":0.2605241118382897,"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."}}