{"id":"W4353048885","doi":"10.1053/j.ro.2023.02.002","title":"Introduction to Radiomics and Artificial Intelligence: A Primer for Radiologists","year":2023,"lang":"en","type":"article","venue":"Seminars in Roentgenology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University Health Centre","funders":"","keywords":"Radiomics; Medicine; Clearance; Applications of artificial intelligence; Radiology; Field (mathematics); Medical imaging; Artificial intelligence; Data science; Health informatics; Deep learning; Medical physics; Informatics; Pathology; Computer science; Public health","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":[0.003140121,0.001381339,0.001289645,0.003375409,0.0009475134,0.005148311,0.002195447,0.006307283,0.01089109],"category_scores_gemma":[0.008182691,0.0007736802,0.001039327,0.002035277,0.005414632,0.006200243,0.002384171,0.01020106,0.007190155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001485106,"about_ca_system_score_gemma":0.00238553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001426644,"about_ca_topic_score_gemma":0.002353315,"domain_scores_codex":[0.9985329,0.0006317132,0.0001757715,0.0001704253,0.0003931167,0.00009601787],"domain_scores_gemma":[0.9914312,0.006493654,0.000254491,0.0002449597,0.001050822,0.0005249874],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007508265,0.0001362366,0.0007080107,0.001704973,0.00004549275,0.0005088408,0.001556571,0.0008663419,0.001087528,0.09035339,0.624508,0.2784495],"study_design_scores_gemma":[0.000008152336,0.00002792299,0.0002700808,0.0008200393,0.000007114256,0.001081502,0.0002246425,0.000245924,0.00009008848,0.04004163,0.9571587,0.00002418119],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"methods","genre_scores_codex":[0.0004955715,0.765142,0.06570651,0.1124125,0.02110267,0.00009508504,0.0002670938,0.0006270774,0.03415156],"genre_scores_gemma":[0.01401432,0.651802,0.09833244,0.1053572,0.07341693,0.0006138603,0.0004286323,0.0005498921,0.05548475],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01089109,"threshold_uncertainty_score":0.03643429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02281702351473435,"score_gpt":0.3340048602337737,"score_spread":0.3111878367190394,"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."}}