{"id":"W4307987954","doi":"10.1111/exsy.13176","title":"Enhancement of clustering techniques by coupling clustering tree and neural network: Application to brain tumour segmentation","year":2022,"lang":"en","type":"article","venue":"Expert Systems","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"European Research Consortium for Informatics and Mathematics","keywords":"Cluster analysis; Computer science; Pattern recognition (psychology); Artificial intelligence; Correlation clustering; Segmentation; Artificial neural network; CURE data clustering algorithm; Data mining; Tree (set theory); Canopy clustering algorithm; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001078185,0.0006251703,0.0004399396,0.001688287,0.0003973606,0.0005422984,0.0006746089,0.001004283,0.0007924719],"category_scores_gemma":[0.001463132,0.0002634477,0.0005277613,0.001772853,0.000339333,0.0005275639,0.0005270133,0.000415651,0.0003752169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006720338,"about_ca_system_score_gemma":0.0005211369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006270187,"about_ca_topic_score_gemma":0.006288057,"domain_scores_codex":[0.9994764,0.0001555924,0.00003036111,0.0001080752,0.0001853385,0.00004417247],"domain_scores_gemma":[0.999272,0.0002087276,0.00006922202,0.00006448413,0.0003559948,0.00002958889],"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":[0.0003380278,0.0001912742,0.002861602,0.0002452234,0.0001967185,0.0002418852,0.0002456705,0.2809509,0.1150562,0.00242464,0.003722135,0.5935256],"study_design_scores_gemma":[0.000009178008,0.00006382274,0.001758133,0.000008833594,0.00002717256,0.00009775106,0.00002656106,0.9676715,0.02831945,0.0007617816,0.00123604,0.00001977076],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1573031,0.001225531,0.8358316,0.0003460377,0.0001268983,0.0001208934,0.0001064181,0.002865063,0.002074606],"genre_scores_gemma":[0.5200688,0.0004093267,0.4770475,0.0001032651,0.00004475924,0.00005182758,0.0001728034,0.0001673913,0.001934448],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006270187,"threshold_uncertainty_score":0.01246738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02701564322791943,"score_gpt":0.287113955424667,"score_spread":0.2600983121967476,"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."}}