{"id":"W4405875244","doi":"10.1007/s11548-024-03309-6","title":"Leveraging domain knowledge for synthetic ultrasound image generation: a novel approach to rare disease AI detection","year":2024,"lang":"en","type":"article","venue":"International Journal of Computer Assisted Radiology and Surgery","topic":"Hemophilia Treatment and Research","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Mohawk College; Ontario Institute for Cancer Research; McMaster University; University of Toronto","funders":"Novo Nordisk Canada","keywords":"Computer science; Domain (mathematical analysis); Image (mathematics); Artificial intelligence; Ultrasound; Computer vision; Data science; Radiology; Medicine; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001117962,0.0008485378,0.0008222861,0.001839627,0.0003244028,0.001002243,0.001361239,0.001562036,0.002330993],"category_scores_gemma":[0.003651298,0.0004053336,0.0009910361,0.001111918,0.0004590251,0.0009462571,0.001385248,0.001303005,0.001335295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003378614,"about_ca_system_score_gemma":0.000943102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00250388,"about_ca_topic_score_gemma":0.002759203,"domain_scores_codex":[0.9993533,0.0001489206,0.00003907582,0.0001699895,0.0002156037,0.00007298368],"domain_scores_gemma":[0.9980252,0.001050083,0.0001216628,0.0002466534,0.0004817905,0.00007458328],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004178215,0.000365204,0.002690195,0.0002455357,0.0001181355,0.0004751344,0.0001352983,0.1472481,0.04559599,0.005148456,0.009229525,0.7883306],"study_design_scores_gemma":[0.00001046813,0.00004961291,0.0004191381,0.00001406209,0.00001983013,0.0002012395,0.00002407781,0.9873288,0.006724705,0.00353633,0.001660172,0.00001154702],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0128978,0.0003501906,0.9826342,0.0003506305,0.000078514,0.00009434213,0.0003463955,0.001980835,0.001267127],"genre_scores_gemma":[0.3284986,0.0006372121,0.6643046,0.0005519189,0.0002323811,0.0001739012,0.002431707,0.0002822792,0.00288748],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00250388,"threshold_uncertainty_score":0.007797956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04515911255416676,"score_gpt":0.3237550246894011,"score_spread":0.2785959121352343,"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."}}