{"id":"W2068848953","doi":"10.1007/s10916-011-9788-9","title":"An Expert Support System for Breast Cancer Diagnosis using Color Wavelet Features","year":2011,"lang":"en","type":"article","venue":"Journal of Medical Systems","topic":"AI in cancer detection","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Saskatchewan Health Research Foundation; Government of Canada","keywords":"Artificial intelligence; Support vector machine; Breast cancer; Pattern recognition (psychology); Computer science; Classifier (UML); Naive Bayes classifier; Wavelet; Artificial neural network; Computer-aided diagnosis; Cancer; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008250602,0.0004415525,0.0005857593,0.0008025622,0.0003108389,0.0007435431,0.001092698,0.0008610102,0.01060991],"category_scores_gemma":[0.002681547,0.0002253585,0.0002765099,0.0004500742,0.0001187515,0.0006157403,0.0004239694,0.0005094405,0.003839761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003357045,"about_ca_system_score_gemma":0.0005165174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001677997,"about_ca_topic_score_gemma":0.001664978,"domain_scores_codex":[0.9996473,0.00004450034,0.00003946807,0.00009689623,0.0001419801,0.00003002418],"domain_scores_gemma":[0.9989212,0.0004073241,0.00006965789,0.0001010519,0.0004240188,0.00007675972],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001391406,0.0005039471,0.003612468,0.0003660942,0.00009144944,0.000983205,0.0002430987,0.01302241,0.07360938,0.002225365,0.03106221,0.872889],"study_design_scores_gemma":[0.0004411186,0.0006230215,0.005762427,0.000112343,0.0001281874,0.001608038,0.0001561429,0.8668267,0.08215397,0.004673577,0.03741232,0.0001021556],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04687927,0.0002902251,0.8862357,0.000474232,0.0001563503,0.0005357496,0.001649605,0.05945808,0.004320798],"genre_scores_gemma":[0.3657576,0.0002687035,0.6176381,0.0003861222,0.00009095494,0.00069239,0.002455652,0.0003749322,0.01233558],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01060991,"threshold_uncertainty_score":0.03549361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05246041481007747,"score_gpt":0.325706219150302,"score_spread":0.2732458043402245,"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."}}