{"id":"W4395463615","doi":"10.18280/isi.290228","title":"Predicting Alzheimer's Disease Using a Modified Grey Wolf Optimizer and Support Vector Machine","year":2024,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Support vector machine; Vector (molecular biology); Disease; Artificial intelligence; Computer science; Pattern recognition (psychology); Machine learning; Biology; Medicine; Recombinant DNA; Pathology; Genetics","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":[0.001180262,0.0007563575,0.001114561,0.0006539068,0.0002585849,0.0006340989,0.0007236945,0.001162659,0.000705733],"category_scores_gemma":[0.002119563,0.0003422187,0.0008588413,0.0005606063,0.0004438973,0.0004975482,0.0004246803,0.0007011517,0.0001435365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004525183,"about_ca_system_score_gemma":0.0007296448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005692575,"about_ca_topic_score_gemma":0.002438725,"domain_scores_codex":[0.9996578,0.0001183052,0.00002974525,0.00008205098,0.0000654145,0.00004666571],"domain_scores_gemma":[0.9994637,0.0003413105,0.0000532601,0.00002800626,0.00008688618,0.00002679179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001245714,0.00006371715,0.003327385,0.00004427474,0.00007718022,0.0001097415,0.00003946426,0.9467799,0.002905527,0.0009766526,0.0004989366,0.04505276],"study_design_scores_gemma":[0.000004173962,0.00002506466,0.0002442018,0.000002339104,0.00000438301,0.000006538176,0.000003145592,0.9991436,0.000267675,0.0002517845,0.00004476285,0.000002334375],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3248793,0.001210858,0.6707057,0.000555016,0.00008258777,0.0001102012,0.0001614051,0.0006013528,0.00169345],"genre_scores_gemma":[0.8874006,0.000213203,0.1101398,0.0001525887,0.00002901819,0.0001322414,0.0002761181,0.00003471201,0.001621804],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005692575,"threshold_uncertainty_score":0.01131886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0973919921525441,"score_gpt":0.3906002282038953,"score_spread":0.2932082360513512,"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."}}