{"id":"W4396514603","doi":"10.1002/mp.17101","title":"Automatic assessment of DWI‐ASPECTS for acute ischemic stroke based on deep learning","year":2024,"lang":"en","type":"article","venue":"Medical Physics","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Shanghai Key Laboratory of Molecular Imaging; National Natural Science Foundation of China","keywords":"Medicine; Stroke (engine); Ischemic stroke; Acute stroke; Computed tomography; Brain ischemia; Neuroimaging; Medical physics; Radiology; Ischemia; Internal medicine","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":[0.0006733525,0.0007892858,0.0006088327,0.00141445,0.0002707767,0.0006193966,0.0005892588,0.0006638128,0.0007675593],"category_scores_gemma":[0.001603753,0.0002509732,0.0005724967,0.0005503291,0.0002147153,0.00064331,0.0005735655,0.0004697255,0.0003002314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005326835,"about_ca_system_score_gemma":0.0007701254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003717275,"about_ca_topic_score_gemma":0.004155079,"domain_scores_codex":[0.9996517,0.00006207249,0.00003492783,0.0001055293,0.00009535957,0.00005044326],"domain_scores_gemma":[0.9995461,0.0001175697,0.00007169306,0.00004148919,0.0001854679,0.00003758047],"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":[0.0005787926,0.0004026149,0.03928462,0.0001370491,0.0001944443,0.0003007026,0.0001187288,0.1306993,0.0265555,0.0007811439,0.005903211,0.7950439],"study_design_scores_gemma":[0.00001488061,0.00007520122,0.005244624,0.0000101802,0.00003839576,0.0001060167,0.00001776629,0.98779,0.005592476,0.0007449753,0.0003511785,0.00001415385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3741113,0.0008321662,0.6193741,0.0003590733,0.00008058637,0.0002589094,0.000575255,0.002565034,0.001843638],"genre_scores_gemma":[0.9001419,0.0003146118,0.09685298,0.0001467498,0.00004623345,0.0001646483,0.0008196634,0.00005256693,0.001460633],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003717275,"threshold_uncertainty_score":0.007391274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01184177145251426,"score_gpt":0.3202291048164424,"score_spread":0.3083873333639282,"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."}}