{"id":"W4401820056","doi":"10.1016/j.ibmed.2024.100161","title":"The impact of artificial intelligence on large vessel occlusion stroke detection and management: A systematic review meta-analysis","year":2024,"lang":"en","type":"review","venue":"Intelligence-Based Medicine","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Meta-analysis; Stroke (engine); Occlusion; Medicine; Artificial intelligence; Computer science; Cardiology; Engineering; Internal medicine; Mechanical engineering","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":[0.01409339,0.00245536,0.01948464,0.004850118,0.0007709475,0.004137285,0.002078526,0.002425983,0.004122837],"category_scores_gemma":[0.04398602,0.001303839,0.03635127,0.006378784,0.0008715836,0.002220735,0.001540665,0.002102596,0.000322605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002385332,"about_ca_system_score_gemma":0.004409845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006484223,"about_ca_topic_score_gemma":0.01212032,"domain_scores_codex":[0.989665,0.004402323,0.003383741,0.0009418628,0.001297573,0.0003095484],"domain_scores_gemma":[0.9676949,0.02552381,0.003881679,0.0007060205,0.001907263,0.0002863769],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.001947348,0.00004374654,0.003314302,0.4985646,0.482262,0.00008513038,0.00009648006,0.0003419408,0.0001190896,0.0001154985,0.0004875934,0.01262228],"study_design_scores_gemma":[0.0005854985,0.0002070899,0.002818504,0.03482981,0.9598907,0.0000625897,0.00003802628,0.0001700408,0.00007181428,0.0001515008,0.001150247,0.00002413115],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004222448,0.9938121,0.0005611004,0.0001824451,0.0001395409,0.0004143184,0.0003910362,0.00002359751,0.0002535064],"genre_scores_gemma":[0.1402965,0.8523869,0.0026031,0.001073614,0.0003484656,0.0021077,0.0007930905,0.00003279491,0.0003577686],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01948464,"threshold_uncertainty_score":0.07453382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1048270524462518,"score_gpt":0.4068079980355511,"score_spread":0.3019809455892992,"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."}}