{"id":"W4213056095","doi":"10.4018/978-1-7998-8929-8.ch002","title":"Optimized Breast Cancer Premature Detection Method With Computational Segmentation","year":2022,"lang":"en","type":"book-chapter","venue":"Advances in healthcare information systems and administration book series","topic":"AI in cancer detection","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mohawk College","funders":"","keywords":"Breast cancer; Mammography; Medicine; Breast tissue; Breast cancer screening; Cancer; Radiology; Segmentation; Oncology; Internal medicine; Artificial intelligence; 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":[0.0003621526,0.0006844054,0.00103817,0.0008856715,0.0004658754,0.00115483,0.001415055,0.0010029,0.006044321],"category_scores_gemma":[0.001161373,0.0004969735,0.001065759,0.000820077,0.0002972301,0.0005349459,0.0007649616,0.0006504931,0.001654648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006240871,"about_ca_system_score_gemma":0.001168313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007009771,"about_ca_topic_score_gemma":0.005066874,"domain_scores_codex":[0.9997461,0.00002790709,0.00001647579,0.00007734416,0.00009399477,0.00003806227],"domain_scores_gemma":[0.9997005,0.0001093982,0.00002391758,0.00003452856,0.0001140369,0.00001757593],"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":[0.0003129609,0.000101634,0.001487989,0.0002559935,0.00009809877,0.0002811919,0.0001060293,0.2895226,0.02499351,0.006404953,0.01761534,0.6588196],"study_design_scores_gemma":[0.000009582822,0.00002287949,0.0003498675,0.00001112959,0.00001716468,0.0001226416,0.00001102469,0.9915859,0.002893243,0.001818984,0.003147818,0.000009881376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01187361,0.0008164725,0.9800311,0.0002452928,0.0001981279,0.0000813178,0.0001772592,0.002639686,0.003937092],"genre_scores_gemma":[0.1879287,0.0009433532,0.7940761,0.0004426322,0.0001927126,0.0002513804,0.001315152,0.0007385549,0.01411144],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007009771,"threshold_uncertainty_score":0.02022028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01132586402500896,"score_gpt":0.2905149505712467,"score_spread":0.2791890865462378,"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."}}