{"id":"W4393373943","doi":"10.1002/pd.6559","title":"Deep‐learning computer vision can identify increased nuchal translucency in the first trimester of pregnancy","year":2024,"lang":"en","type":"article","venue":"Prenatal Diagnosis","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Imperial Bank of Commerce (Canada); Vector Institute; Canadian Institute for Advanced Research; Mount Sinai Hospital; Centre for Social Innovation; Hospital for Sick Children; University of Toronto","funders":"Mount Sinai Health System","keywords":"Fetus; Segmentation; Medicine; 3D ultrasound; Pregnancy; Ultrasound; Fetal head; Convolutional neural network; Prenatal diagnosis; Gestation; Obstetrics; Nuclear medicine; Artificial intelligence; Radiology; Computer science; Biology","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":[0.00103058,0.0006845177,0.0003307838,0.001350358,0.0001718663,0.0006658955,0.0003822706,0.0007404897,0.00132862],"category_scores_gemma":[0.004285248,0.0002088088,0.0004199709,0.0004587485,0.0002494165,0.0004185078,0.0004329855,0.0005047794,0.0005716804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005956682,"about_ca_system_score_gemma":0.0005068717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006167404,"about_ca_topic_score_gemma":0.005935338,"domain_scores_codex":[0.9996294,0.00009640359,0.00002304607,0.0001058589,0.00008192394,0.00006345007],"domain_scores_gemma":[0.9989104,0.0005530669,0.0001857382,0.00006646502,0.0002301475,0.00005408786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009017907,0.0003417692,0.09598709,0.000227812,0.0003027448,0.0004343106,0.0001286335,0.1994348,0.03505258,0.00128405,0.007051891,0.6588525],"study_design_scores_gemma":[0.0000166839,0.0001224658,0.02484557,0.00005122974,0.0000411533,0.0001791788,0.00003063691,0.9628745,0.009290575,0.001368246,0.001164797,0.00001500974],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7762468,0.003376623,0.207569,0.00101871,0.0001672332,0.0001062739,0.001073706,0.002882116,0.007559531],"genre_scores_gemma":[0.956265,0.0006313151,0.04010446,0.0001801938,0.00004940112,0.0000501126,0.0009479679,0.00006142349,0.001710123],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006167404,"threshold_uncertainty_score":0.012263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01446465153376643,"score_gpt":0.2826172142797528,"score_spread":0.2681525627459864,"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."}}