{"id":"W4385751831","doi":"10.1002/alz.13412","title":"Artificial intelligence for diagnostic and prognostic neuroimaging in dementia: A systematic review","year":2023,"lang":"en","type":"review","venue":"Alzheimer s & Dementia","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"NIHR Cambridge Biomedical Research Centre; National Institutes of Health; National Health and Medical Research Council; Courtois Foundation; National Institute for Health and Care Research; Bundesministerium für Bildung und Forschung; University of Bristol; Deutsche Forschungsgemeinschaft; Comisión Nacional de Investigación Científica y Tecnológica; Department of Health and Social Care; Engineering and Physical Sciences Research Council; EU Joint Programme – Neurodegenerative Disease Research; Medical Research Council; Alzheimer's Association","keywords":"Neuroimaging; Dementia; Artificial intelligence; Modalities; Machine learning; Discriminative model; Disease; Alzheimer's Disease Neuroimaging Initiative; Computer science; Medicine; Data science; Psychiatry; Pathology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001985707,0.0006787174,0.003083386,0.0006291537,0.0001341356,0.0001428986,0.000334333,0.0001621827,0.000100851],"category_scores_gemma":[0.003232558,0.0005562725,0.0005550048,0.0009930014,0.0001311489,0.0001343417,0.0003287145,0.0005110527,0.000327171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002247048,"about_ca_system_score_gemma":0.0003403817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001772408,"about_ca_topic_score_gemma":0.00002152368,"domain_scores_codex":[0.9948137,0.0004555537,0.002179093,0.001006984,0.0006519667,0.0008926712],"domain_scores_gemma":[0.9959474,0.002510909,0.0005167379,0.000557017,0.0002097198,0.0002582567],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.000006840366,0.0001759017,0.0002184326,0.6344383,0.01171274,0.0001978138,0.00001744265,2.903239e-8,2.036867e-7,0.0001257766,0.0002668883,0.3528396],"study_design_scores_gemma":[0.0001592961,0.00031686,0.0001029305,0.6465863,0.3344961,0.0001267371,0.00003238777,0.00006040712,0.000005794161,0.0002912565,0.01732208,0.0004998168],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000003635811,0.9790004,0.0005201329,0.0002315349,0.000214539,0.01981601,0.00003931156,0.0001016071,0.00007278696],"genre_scores_gemma":[0.0006178517,0.9888757,0.000324129,0.0003229679,0.0001131708,0.009255566,0.0003215782,0.0001525643,0.00001650641],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.3523398,"threshold_uncertainty_score":0.9996889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1309578454209125,"score_gpt":0.4093633904839638,"score_spread":0.2784055450630513,"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."}}