{"id":"W4409244438","doi":"10.1148/radiol.240775","title":"Deep Learning Applications in Imaging of Acute Ischemic Stroke: A Systematic Review and Narrative Summary","year":2025,"lang":"en","type":"review","venue":"Radiology","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Stroke (engine); Deep learning; Acute stroke; Ischemic stroke; Segmentation; Narrative review; Artificial intelligence; Lesion; Test (biology); Medical physics; Ischemia; Intensive care medicine; Internal medicine; Surgery","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004443766,0.001222642,0.004318389,0.006010112,0.0004138699,0.002108009,0.001327135,0.001506817,0.005063905],"category_scores_gemma":[0.02359239,0.0005096513,0.005470803,0.00605275,0.0005190028,0.001579412,0.00110355,0.001100524,0.0004665889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001603404,"about_ca_system_score_gemma":0.005625612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004730585,"about_ca_topic_score_gemma":0.01338668,"domain_scores_codex":[0.9973983,0.0006805018,0.001052474,0.0002407589,0.0005224791,0.0001055431],"domain_scores_gemma":[0.9848799,0.01161871,0.001943145,0.000186753,0.00126395,0.0001074982],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.000225211,0.00002329028,0.0008769953,0.8862199,0.006072588,0.00007389933,0.0001007493,0.00023313,0.0001597633,0.0004679667,0.003999197,0.1015472],"study_design_scores_gemma":[0.0001930648,0.00021986,0.00447099,0.8897493,0.05697924,0.0004447736,0.0001634549,0.0003089239,0.0002728249,0.0009752684,0.04617316,0.00004907952],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004288809,0.998442,0.000177567,0.0002724814,0.00007145743,0.00009216191,0.0002600676,0.000006373336,0.0002490746],"genre_scores_gemma":[0.005386882,0.9930214,0.0004345507,0.0005506718,0.0001056086,0.0002131533,0.000180304,0.000004073177,0.0001032988],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006010112,"threshold_uncertainty_score":0.02350116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0105874277278563,"score_gpt":0.3123464907609305,"score_spread":0.3017590630330741,"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."}}