{"id":"W4387455326","doi":"10.23977/acss.2023.070803","title":"Review of deep learning-driven MRI brain tumor detection and segmentation methods","year":2023,"lang":"en","type":"article","venue":"Advances in Computer Signals and Systems","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Segmentation; Deep learning; Artificial intelligence; Computer science; Brain tumor; Magnetic resonance imaging; Machine learning; Pattern recognition (psychology); Medicine; Radiology; Pathology","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":[0.001106474,0.0009809732,0.0008993311,0.001714062,0.0002352636,0.0009013698,0.001208737,0.0008915454,0.002289877],"category_scores_gemma":[0.002440023,0.0005357244,0.0009983795,0.001983668,0.0003005023,0.001164465,0.0005714608,0.0009264533,0.001346176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006379131,"about_ca_system_score_gemma":0.001631279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003142047,"about_ca_topic_score_gemma":0.003128374,"domain_scores_codex":[0.9995219,0.00007122811,0.00008176769,0.0001093063,0.0001863311,0.00002953791],"domain_scores_gemma":[0.9991094,0.0004388399,0.00006336737,0.00003746591,0.0003206114,0.00003019019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007056077,0.00004872654,0.0007035218,0.006266622,0.0001564295,0.0001112812,0.00005075787,0.0122538,0.003312777,0.004806874,0.0214709,0.9507478],"study_design_scores_gemma":[0.00005162747,0.0004724125,0.005248109,0.005378496,0.0008682795,0.002239698,0.0001186462,0.1625934,0.02102548,0.02134908,0.78044,0.0002148427],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004168052,0.7922676,0.1917145,0.002036324,0.0009737907,0.0001076734,0.0008153049,0.0007298723,0.007186925],"genre_scores_gemma":[0.0343558,0.8542366,0.0976304,0.001592855,0.001476375,0.0001787019,0.002614812,0.0002384576,0.007676025],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003142047,"threshold_uncertainty_score":0.007660449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03945141434356894,"score_gpt":0.352475188624321,"score_spread":0.313023774280752,"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."}}