{"id":"W4323035249","doi":"10.1002/9781119790686.ch34","title":"AI for Medical Image Processing","year":2023,"lang":"en","type":"other","venue":"AI in Clinical Medicine","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Toronto","funders":"","keywords":"Convolutional neural network; Computer science; Scope (computer science); Quality assurance; Medical imaging; Image quality; Image processing; Medical physics; Artificial intelligence; Artificial neural network; Quality (philosophy); Image (mathematics); Computer vision; Medicine; 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":[0.00191832,0.001235471,0.0008379858,0.002603334,0.0007509478,0.005233064,0.001617985,0.002920091,0.046394],"category_scores_gemma":[0.007114584,0.0003911119,0.0007755946,0.002957426,0.002571923,0.003318259,0.002644608,0.00400276,0.03364022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001400631,"about_ca_system_score_gemma":0.001722131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001257024,"about_ca_topic_score_gemma":0.0007158042,"domain_scores_codex":[0.9978527,0.0005414998,0.0001589908,0.000354251,0.0009985269,0.00009411471],"domain_scores_gemma":[0.9972107,0.001353472,0.000189115,0.0005036487,0.0005959579,0.0001471946],"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":[0.00004582535,0.000035266,0.0002509311,0.001076001,0.00004537555,0.0001576288,0.0001770012,0.003545701,0.001784261,0.424462,0.1122769,0.4561432],"study_design_scores_gemma":[0.00001192222,0.00003155553,0.0002224066,0.0005010468,0.00001584041,0.0004375541,0.00005402576,0.0141833,0.00117945,0.2523449,0.7309867,0.00003125489],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001211819,0.07797762,0.6584501,0.01729056,0.00575147,0.0003341174,0.001136809,0.006024149,0.2318233],"genre_scores_gemma":[0.07141268,0.09970821,0.6199914,0.007263448,0.009573827,0.001277214,0.002458843,0.001802429,0.1865119],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.046394,"threshold_uncertainty_score":0.1552033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04139267117788451,"score_gpt":0.4816122287065652,"score_spread":0.4402195575286807,"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."}}