{"id":"W4388441521","doi":"10.18280/isi.280518","title":"Automated Identification and Classification of Brain Tumors Using Hybrid Machine Learning Models and MRI Imaging","year":2023,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Artificial intelligence; Computer science; Neuroimaging; Brain tumor; Machine learning; Pattern recognition (psychology); Neuroscience; Medicine; Psychology; Pathology; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007067699,0.0007927592,0.0006113895,0.001535294,0.0002272047,0.001187074,0.000807304,0.001044299,0.000595541],"category_scores_gemma":[0.001170248,0.0003075736,0.0009287215,0.000997017,0.0003424586,0.0009249565,0.000553925,0.0006115962,0.0006492235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005326719,"about_ca_system_score_gemma":0.0005571311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004114868,"about_ca_topic_score_gemma":0.004833422,"domain_scores_codex":[0.9994226,0.0001111023,0.00003631811,0.0001573116,0.0002000606,0.0000726529],"domain_scores_gemma":[0.9996099,0.0001224414,0.00008000837,0.00007388817,0.00009940399,0.00001451488],"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":[0.0001995932,0.0003285025,0.006312255,0.0001440172,0.0002008552,0.0002458684,0.00008054548,0.3507038,0.03918212,0.00355494,0.003944947,0.5951027],"study_design_scores_gemma":[0.000004220249,0.00005837942,0.001601271,0.00001464653,0.00001938539,0.00009383291,0.00002116622,0.9890885,0.0059338,0.001852418,0.001295903,0.00001639403],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1123753,0.002313878,0.878534,0.0005923493,0.0001477516,0.000106756,0.0003062346,0.002664878,0.002958834],"genre_scores_gemma":[0.7146245,0.00176366,0.2767219,0.0003731721,0.0001497558,0.0001607158,0.001285882,0.0001008178,0.004819556],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004114868,"threshold_uncertainty_score":0.00818181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04145965148511233,"score_gpt":0.2711386075190708,"score_spread":0.2296789560339584,"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."}}