{"id":"W1966130221","doi":"10.5539/gjhs.v7n4p392","title":"Prediction of Breast Cancer Survival Through Knowledge Discovery in Databases","year":2015,"lang":"en","type":"article","venue":"Global Journal of Health Science","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Iran University of Medical Sciences","keywords":"Breast cancer; Context (archaeology); Medicine; IBM; Predictive modelling; Cancer; Oncology; Machine learning; Computer science; Internal medicine; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005296916,0.0005530482,0.001024893,0.005769503,0.0004955275,0.002666613,0.001148986,0.0007701864,0.0006295888],"category_scores_gemma":[0.01771799,0.0003141635,0.00114691,0.004730246,0.000262919,0.001830033,0.001180917,0.001011839,0.0004120368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007209796,"about_ca_system_score_gemma":0.00189509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005872171,"about_ca_topic_score_gemma":0.005048728,"domain_scores_codex":[0.9967674,0.001198955,0.0005356583,0.0005005903,0.0008005,0.0001968631],"domain_scores_gemma":[0.9887717,0.008361977,0.000926292,0.0007772408,0.0009779115,0.0001848721],"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":[0.0009895703,0.001383817,0.2539429,0.001490514,0.000900968,0.001161312,0.0007155419,0.09796178,0.003644761,0.007110414,0.01067573,0.6200227],"study_design_scores_gemma":[0.0001097425,0.0005253955,0.05941821,0.0004734189,0.000621827,0.0008142628,0.0009668287,0.8855506,0.00981403,0.028956,0.01263518,0.0001145858],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5428081,0.007323447,0.4093947,0.004532149,0.0002113338,0.0009910036,0.02545245,0.003025128,0.006261735],"genre_scores_gemma":[0.7982264,0.003371703,0.1817987,0.0002701454,0.0001043815,0.0003796242,0.01513081,0.00003417641,0.0006840394],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005872171,"threshold_uncertainty_score":0.02801311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4373148152868181,"score_gpt":0.5608005764447357,"score_spread":0.1234857611579176,"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."}}