{"id":"W4400574320","doi":"10.1016/j.eclinm.2024.102725","title":"Robust and interpretable AI-guided marker for early dementia prediction in real-world clinical settings","year":2024,"lang":"en","type":"article","venue":"EClinicalMedicine","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Canadian Institutes of Health Research; Bristol-Myers Squibb; Royal Society; Wellcome Trust; National Institute on Aging; National Institute for Health and Care Research; Northern California Institute for Research and Education; BioClinica; Biogen; Pfizer; NIHR Cambridge Biomedical Research Centre; Novartis Pharmaceuticals Corporation; Engineering and Physical Sciences Research Council; Eli Lilly and Company; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Medicine; Dementia; Artificial intelligence; Internal medicine; Disease","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004920256,0.0002189654,0.0006245262,0.0004069159,0.00006227249,0.00006874114,0.0001023856,0.000170582,0.0009896564],"category_scores_gemma":[0.00143661,0.0001717965,0.0001924344,0.0004910887,0.000293207,0.0001951315,0.0001249635,0.0007776239,0.00006730257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006493404,"about_ca_system_score_gemma":0.0002108522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001121709,"about_ca_topic_score_gemma":0.0000692031,"domain_scores_codex":[0.9967403,0.0001703173,0.001368767,0.0007583164,0.0004472689,0.000514975],"domain_scores_gemma":[0.9976808,0.001407055,0.00008120041,0.0002865846,0.0001890703,0.0003552196],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008115676,0.0002820567,0.9025897,0.0004450155,0.000338592,0.0001262871,0.0000848481,5.289236e-7,0.000109918,0.0001751474,0.07024952,0.0247868],"study_design_scores_gemma":[0.005501553,0.00228991,0.9274063,0.001862768,0.0005790518,0.00003021692,0.00007365329,0.01352469,0.00004395176,0.0006560687,0.04788944,0.000142379],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9505486,0.001354208,0.004955797,0.02062563,0.001275439,0.002215881,0.00003973325,0.0002405798,0.01874409],"genre_scores_gemma":[0.9787201,0.0008661506,0.001541228,0.003125589,0.001062357,0.0001923923,0.000113281,0.00004951444,0.01432936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02817148,"threshold_uncertainty_score":0.9999236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07428144383149617,"score_gpt":0.4296510624789388,"score_spread":0.3553696186474426,"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."}}