{"id":"W4220680585","doi":"10.3390/cancers14051349","title":"Advancements in Oncology with Artificial Intelligence—A Review Article","year":2022,"lang":"en","type":"review","venue":"Cancers","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Medicine; Medical physics; Standardization; Breast cancer; Grading (engineering); Generalizability theory; Precision medicine; Personalized medicine; Colorectal cancer; Neuroimaging; Cancer; Oncology; Artificial intelligence; Internal medicine; Pathology; Bioinformatics; Computer science; Psychology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005080015,0.000213836,0.001415231,0.0001363463,0.00004508793,0.000006649865,0.0001563243,0.00007077673,0.001965425],"category_scores_gemma":[0.0002607917,0.0001570947,0.0001469413,0.0006011142,0.0001030964,0.00002811425,0.00005443304,0.001116131,0.00003830938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0033889,"about_ca_system_score_gemma":0.002406748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007477574,"about_ca_topic_score_gemma":0.0000163018,"domain_scores_codex":[0.9983667,0.0001420152,0.0005594229,0.0003621869,0.000268503,0.0003011758],"domain_scores_gemma":[0.9992031,0.000130197,0.0002340949,0.0002723283,0.00001688674,0.0001433269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000177594,0.00002267928,0.000006317775,0.01671388,0.00005502938,0.0002717031,0.00003050414,0.00004113675,8.906406e-8,0.00009837864,0.0007561056,0.9819864],"study_design_scores_gemma":[0.0001031161,0.0002446792,4.491511e-7,0.03710636,0.0005063058,0.0001321321,0.00004940294,0.0001806735,1.882457e-7,0.00003574227,0.9614899,0.000151083],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000003451243,0.9942978,0.0002175945,0.0005352973,0.0003186208,0.0008968194,0.000003682442,0.00002402947,0.003702696],"genre_scores_gemma":[0.000003666962,0.9965084,0.0006105634,0.002033775,0.0001510181,0.0003845149,0.00006637942,0.00004230013,0.0001993614],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9818353,"threshold_uncertainty_score":0.9989469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0806369913517267,"score_gpt":0.4364614543406138,"score_spread":0.3558244629888871,"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."}}