{"id":"W4409584267","doi":"10.1093/rap/rkae147","title":"AI for imaging evaluation in rheumatology: applications of radiomics and computer vision—current status, future prospects and potential challenges","year":2025,"lang":"en","type":"review","venue":"Rheumatology Advances in Practice","topic":"Rheumatoid Arthritis Research and Therapies","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network","funders":"Technische Universität München","keywords":"Medicine; Radiomics; Modalities; Rheumatology; Immune status; Medical physics; Medical imaging; Intensive care medicine; Internal medicine; Radiology; Immune system; Immunology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001283682,0.0003430855,0.001901005,0.0007669821,0.00009284831,0.00002839766,0.0001358449,0.0002571101,0.000004837153],"category_scores_gemma":[0.0009824854,0.0003084994,0.0000988741,0.000331025,0.000349532,0.0006113327,0.000138914,0.0007399453,0.00000116359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001121008,"about_ca_system_score_gemma":0.0007128065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001273034,"about_ca_topic_score_gemma":0.00005962212,"domain_scores_codex":[0.9969987,0.000625313,0.0009891597,0.0006917301,0.000263301,0.000431855],"domain_scores_gemma":[0.9962814,0.002330396,0.0006176127,0.0003380025,0.0003325768,0.00009995862],"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":[0.0002242934,0.0002459696,0.0006033573,0.03755819,0.0001049042,0.000008725659,0.0002277905,0.000002630354,8.746397e-8,0.01873351,0.00005088066,0.9422396],"study_design_scores_gemma":[0.003375741,0.0001697314,0.0001033176,0.02590489,0.000161178,0.002097693,0.0004179468,0.00144429,2.692261e-7,0.003178548,0.9628924,0.0002539597],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00005195581,0.9915196,0.002458643,0.001407164,0.000431542,0.00399827,0.00004495568,0.00002250251,0.00006538881],"genre_scores_gemma":[0.000574735,0.9925578,0.005167304,0.00002316949,0.00002149969,0.001475261,0.0001493278,0.00002855945,0.000002403493],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9628416,"threshold_uncertainty_score":0.9999367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01489335528903889,"score_gpt":0.4048691339774202,"score_spread":0.3899757786883813,"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."}}