{"id":"W4310584357","doi":"10.1109/icaee53772.2022.9962049","title":"Deep Learning based Method for Alzheimer’s Disease Stages Classification using MRI Images","year":2022,"lang":"en","type":"article","venue":"2022 2nd International Conference on Advanced Electrical Engineering (ICAEE)","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Rimouski","funders":"","keywords":"Convolutional neural network; Computer science; Artificial intelligence; Deep learning; Dementia; Disease; Machine learning; Magnetic resonance imaging; Medical imaging; Medicine; Pathology; Radiology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003225262,0.0002454031,0.000196341,0.0003920792,0.0004477741,0.0001174901,0.0004942183,0.00004427689,0.0007549589],"category_scores_gemma":[0.001313408,0.0002789619,0.0001437285,0.0005940737,0.00003312443,0.0002278569,0.00007015174,0.0006683077,0.000008933405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004516707,"about_ca_system_score_gemma":0.0001209224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003360672,"about_ca_topic_score_gemma":3.478817e-7,"domain_scores_codex":[0.9976431,0.0002054448,0.0003630632,0.0007352261,0.000681944,0.0003712179],"domain_scores_gemma":[0.9986278,0.0005879629,0.0002183886,0.0002448648,0.000142997,0.0001779391],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002640949,0.0001194705,0.00002190548,0.000007454481,0.00001307289,0.000004233535,0.00001795705,0.4449274,0.4821849,0.04989656,0.00005973832,0.02248327],"study_design_scores_gemma":[0.0005907899,0.0001998914,0.0006016602,0.00001013216,0.00002461383,0.000007648204,0.00003902085,0.9377344,0.04444922,0.0005062203,0.01554214,0.0002942577],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003122707,0.00008773901,0.9915326,0.002577509,0.000777694,0.0005924172,0.00006907537,0.0003886653,0.0008515497],"genre_scores_gemma":[0.9850425,0.00005017701,0.0127781,0.0006545702,0.0001054966,0.0006008279,0.00008563523,0.00005862328,0.0006240935],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9819198,"threshold_uncertainty_score":0.9999663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0645936934472161,"score_gpt":0.3356673500920841,"score_spread":0.271073656644868,"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."}}