{"id":"W4377234508","doi":"10.18280/ts.400203","title":"Deep Learning-Based Multi-Feature Auxiliary Diagnosis Method for Early Detection of Ischemic Stroke","year":2023,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Ischemic stroke; Feature (linguistics); Computer science; Stroke (engine); Pattern recognition (psychology); Machine learning; Medicine; Cardiology; Ischemia; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000465169,0.0001513495,0.0001630814,0.0002168964,0.0002061282,0.00003415273,0.000162423,0.00009931681,0.000113347],"category_scores_gemma":[0.0003737983,0.0001506976,0.0001636458,0.0005101199,0.00005506777,0.0001146467,0.00001783123,0.0002151754,0.00003474618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005283848,"about_ca_system_score_gemma":0.00002465077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001231953,"about_ca_topic_score_gemma":0.00001526241,"domain_scores_codex":[0.9985661,0.0002103217,0.0002598665,0.000406594,0.000301147,0.0002559848],"domain_scores_gemma":[0.9988461,0.0006784878,0.0001915637,0.0001419689,0.00006841304,0.00007349871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001333504,0.0001094766,0.000713272,0.0000529496,0.000008868577,0.000001549919,0.0001862159,0.003431311,0.9573444,0.00002387757,0.0003508896,0.03764386],"study_design_scores_gemma":[0.0009474222,0.0002430042,0.01105587,0.00001108911,0.00002180449,0.000001431443,0.00008382788,0.3028821,0.6781284,0.000009119698,0.006507922,0.0001079861],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4007578,0.00001765848,0.5970994,0.0005872645,0.0002482847,0.0007361536,0.0000418732,0.0003829878,0.0001286294],"genre_scores_gemma":[0.9959617,0.00001010524,0.002365459,0.0002104327,0.00007625905,0.0005656601,0.00001466244,0.00002922729,0.0007665171],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5952039,"threshold_uncertainty_score":0.6145271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04215658964903937,"score_gpt":0.2965983699834662,"score_spread":0.2544417803344268,"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."}}