{"id":"W2083660024","doi":"10.2200/s00325ed1v01y201012bme039","title":"Modeling and Analysis of Shape with Applications in Computer-Aided Diagnosis of Breast Cancer","year":2011,"lang":"en","type":"article","venue":"Synthesis lectures on biomedical engineering","topic":"AI in cancer detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Research Services, University of Calgary; Fundação de Amparo à Pesquisa do Estado de Minas Gerais; Fondation pour la Recherche Médicale; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Natural Sciences and Engineering Research Council of Canada; Alberta Heritage Foundation for Medical Research; Universidade Federal de Uberlândia; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Computer science; Artificial intelligence; Mammography; Segmentation; Observer (physics); Computer vision; Pattern recognition (psychology); Artifact (error); Shape analysis (program analysis); Noise (video); Active contour model; Breast cancer; Image segmentation; Image (mathematics); 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001248188,0.0001193502,0.0002975923,0.0006774397,0.000018787,0.000008331722,0.000274379,0.00006801145,0.00002088355],"category_scores_gemma":[0.00001942915,0.00009477598,0.00005122199,0.001481813,0.00005249046,0.00007387804,0.00005553954,0.00009696078,1.310989e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004913768,"about_ca_system_score_gemma":0.00002628086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004039704,"about_ca_topic_score_gemma":0.00004789095,"domain_scores_codex":[0.9990892,0.00001738131,0.0002414419,0.0002725469,0.0002300403,0.0001493666],"domain_scores_gemma":[0.9993593,0.0002165485,0.0000625179,0.0002513576,0.00003854679,0.00007169336],"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":[0.00004495872,0.0002605094,0.01188296,0.0002125024,0.0008308376,0.000003709451,0.001276921,0.6875514,0.002614865,0.001200414,0.000003297564,0.2941176],"study_design_scores_gemma":[0.00007477833,0.00004428679,0.03462435,0.0001171011,0.00008679119,0.000001703483,0.00000473514,0.958762,0.006149725,0.00003115179,0.000005156303,0.00009815083],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.221202,0.0001135523,0.7784443,0.00006948753,0.00002701186,0.00008404356,0.00001358356,0.00003974446,0.000006176787],"genre_scores_gemma":[0.9684616,0.00006991575,0.03128639,0.00001558012,0.00001922527,0.0001376778,8.557449e-7,0.000008604819,1.244202e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7472596,"threshold_uncertainty_score":0.3864852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01135205900808972,"score_gpt":0.2153129973328208,"score_spread":0.2039609383247311,"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."}}