{"id":"W4292874285","doi":"10.1109/memea54994.2022.9856496","title":"Classification of Ultrasound Breast Images Using Fused Ensemble of Deep Learning Classifiers","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","topic":"AI in cancer detection","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Artificial intelligence; Autoencoder; Deep learning; Transfer of learning; Computer science; Ensemble learning; Machine learning; Pattern recognition (psychology); Convolutional neural network; Contextual image classification; Source code; Image (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009808848,0.0001429555,0.0001885919,0.0001957648,0.000335642,0.00004065523,0.0008477359,0.00006410436,0.0002076209],"category_scores_gemma":[0.00007303046,0.0001521105,0.00007825023,0.0004979837,0.0001366665,0.0001902118,0.0001567933,0.000349309,0.000003220379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003441744,"about_ca_system_score_gemma":0.000090911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006355662,"about_ca_topic_score_gemma":0.000006868729,"domain_scores_codex":[0.9966338,0.0001790434,0.0005228998,0.000459676,0.002028832,0.0001757039],"domain_scores_gemma":[0.9986262,0.000180906,0.0004600406,0.0003386713,0.0002729181,0.0001212072],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007015542,0.0005602145,0.01070112,0.00004682628,0.0001756505,0.000001314954,0.0002960792,0.006337899,0.8820859,0.008664723,0.0003231528,0.09073693],"study_design_scores_gemma":[0.006009937,0.001324185,0.05776763,0.000280652,0.0002540606,0.0005806806,0.001782924,0.6651246,0.2095443,0.006710951,0.04899041,0.001629701],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07546049,0.0001132352,0.9158898,0.002578745,0.001063625,0.0006012436,0.00005133388,0.00009407783,0.004147427],"genre_scores_gemma":[0.9969744,0.00006611057,0.00230068,0.0001357684,0.0001419109,0.0002734483,0.00002209465,0.00001533318,0.00007025056],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9215139,"threshold_uncertainty_score":0.6202884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03827799512939024,"score_gpt":0.2945394759490936,"score_spread":0.2562614808197033,"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."}}