{"id":"W4399663792","doi":"10.1093/braincomms/fcae208","title":"Predicting conversion from mild cognitive impairment to Alzheimer’s disease: a multimodal approach","year":2024,"lang":"en","type":"article","venue":"Brain Communications","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundação para a Ciência e a Tecnologia; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Janssen Alzheimer Immunotherapy Research And Development; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Neuroimaging; Modalities; Cognition; Diffusion MRI; Cognitive impairment; Disease; Modality (human–computer interaction); Alzheimer's disease; Magnetic resonance imaging; Psychology; Artificial intelligence; Medicine; Computer science; Neuroscience; Pathology; Radiology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001214504,0.0009483009,0.0008664957,0.00149069,0.0003386769,0.000960234,0.0005135623,0.0007978315,0.0009620975],"category_scores_gemma":[0.002381593,0.0001657332,0.001063992,0.000592316,0.0002167219,0.000515627,0.0007740404,0.0008793699,0.0002983837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003979123,"about_ca_system_score_gemma":0.0005165381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007784403,"about_ca_topic_score_gemma":0.009301467,"domain_scores_codex":[0.9995922,0.0001178454,0.00003419169,0.0001285022,0.00005931702,0.00006782833],"domain_scores_gemma":[0.9995002,0.0001925261,0.00007821267,0.0000595529,0.0001057458,0.00006375021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002065696,0.0009872565,0.4082656,0.0001835826,0.001414862,0.001066359,0.0003561009,0.1906396,0.01933027,0.0006829675,0.003825991,0.3711817],"study_design_scores_gemma":[0.00002886529,0.0004449479,0.1076318,0.00006325573,0.0004005357,0.0004801948,0.0002511051,0.882277,0.004734646,0.002687612,0.0009396083,0.00006045063],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9371645,0.001213114,0.05705166,0.0006515992,0.00005162627,0.00008042745,0.001476006,0.0004347216,0.001876481],"genre_scores_gemma":[0.9904969,0.0001736785,0.008113185,0.00005753647,0.00003640242,0.00002335579,0.000749479,0.0000108268,0.0003385971],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007784403,"threshold_uncertainty_score":0.01547819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06036539203858021,"score_gpt":0.3719816484712481,"score_spread":0.3116162564326679,"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."}}