{"id":"W4386347024","doi":"10.1002/alz.13390","title":"Artificial intelligence for biomarker discovery in Alzheimer's disease and dementia","year":2023,"lang":"en","type":"review","venue":"Alzheimer s & Dementia","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":118,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"NIHR Maudsley Biomedical Research Centre; National Institutes of Health; Alzheimer’s Research UK; National Health and Medical Research Council; Courtois Foundation; British Heart Foundation; Engineering and Physical Sciences Research Council; National Institute for Health and Care Research; Alzheimer's Society; Motor Neurone Disease Association; Medical Research Council; National Institute on Aging; Alzheimer's Association","keywords":"Computer science; Artificial intelligence; Machine learning; Dementia; Data science; Biomarker discovery; Set (abstract data type); Biomarker; Data set; Big data; Disease; Data mining; Medicine; Biology","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":[0.001249761,0.0007582539,0.001274597,0.000675527,0.0002700672,0.0006426749,0.001724162,0.0002767314,0.00002508841],"category_scores_gemma":[0.0001689029,0.0007136759,0.0004564658,0.001133426,0.000127304,0.0007057711,0.001277517,0.0005164169,0.0001541218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001902472,"about_ca_system_score_gemma":0.0005167787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002156792,"about_ca_topic_score_gemma":0.0001766221,"domain_scores_codex":[0.994812,0.0004931474,0.001598418,0.001651823,0.000486982,0.0009577046],"domain_scores_gemma":[0.9969059,0.0007939924,0.0006006042,0.001259674,0.00008077287,0.0003591127],"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":[0.000009296508,0.00005654487,0.0001061877,0.001142405,0.00776802,0.00004395771,0.00006122558,0.000009020511,6.643415e-8,0.01279252,0.0004039824,0.9776068],"study_design_scores_gemma":[0.0001492507,0.0001510142,0.0004972106,0.005980985,0.06323807,0.00001852652,0.00001976137,0.01686276,0.000006031111,0.01381339,0.8971937,0.002069351],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000001603378,0.9593313,0.03622975,0.000385995,0.001302411,0.002390414,0.0000924718,0.0002378819,0.00002812158],"genre_scores_gemma":[0.001195217,0.987969,0.008873574,0.0001445278,0.0002388111,0.00117699,0.0002532468,0.0001426738,0.000005961736],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9755374,"threshold_uncertainty_score":0.9995314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1493578978630939,"score_gpt":0.3918913112221599,"score_spread":0.242533413359066,"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."}}