{"id":"W4300687540","doi":"10.1016/j.semradonc.2022.06.005","title":"Artificial Intelligence for Outcome Modeling in Radiotherapy","year":2022,"lang":"en","type":"review","venue":"Seminars in Radiation Oncology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre","funders":"National Institutes of Health","keywords":"Medicine; Radiation therapy; Outcome (game theory); Medical physics; Personalized medicine; Modality (human–computer interaction); Artificial intelligence; Radiation oncology; Machine learning; Precision medicine; Bioinformatics; Computer science; Radiology; Pathology","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":[0.002037855,0.001075677,0.002125276,0.001489031,0.0001890071,0.001735545,0.001784716,0.001696091,0.003101328],"category_scores_gemma":[0.003625067,0.0004063679,0.001358089,0.002302524,0.001127067,0.001505131,0.0009023869,0.003158547,0.001101673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001228637,"about_ca_system_score_gemma":0.001379283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002376988,"about_ca_topic_score_gemma":0.002615763,"domain_scores_codex":[0.9994294,0.0002489044,0.00005262169,0.00008417851,0.0001585093,0.00002642154],"domain_scores_gemma":[0.9978735,0.001802491,0.0001170065,0.00005029657,0.0001275274,0.00002907873],"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":[0.00004757154,0.00009428134,0.0004717314,0.01245841,0.0004160705,0.000137559,0.00005409358,0.01024396,0.0002237943,0.03041598,0.01796104,0.9274755],"study_design_scores_gemma":[0.0001133462,0.0002611683,0.00374897,0.02967045,0.001034819,0.001552443,0.0001483647,0.03132438,0.0009470486,0.1833066,0.7477158,0.0001766139],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001743898,0.9941458,0.003373995,0.0009015425,0.0001981939,0.000007747551,0.00002724497,0.00002284438,0.001148301],"genre_scores_gemma":[0.004781468,0.9901751,0.003449224,0.0004895333,0.0004637771,0.0000202908,0.00006206913,0.000009939702,0.0005486561],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003101328,"threshold_uncertainty_score":0.01077735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1332469376436569,"score_gpt":0.4720214475964833,"score_spread":0.3387745099528265,"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."}}