{"id":"W3016809691","doi":"10.1007/s00259-020-04814-x","title":"Individual brain metabolic connectome indicator based on Kullback-Leibler Divergence Similarity Estimation predicts progression from mild cognitive impairment to Alzheimer’s dementia","year":2020,"lang":"en","type":"article","venue":"European Journal of Nuclear Medicine and Molecular Imaging","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":96,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; National Key Research and Development Program of China; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; H. Lundbeck A/S; Servier; National Natural Science Foundation of China; Eisai; Genentech; IXICO; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Foundation for the National Institutes of Health; Science and Technology Commission of Shanghai Municipality; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Alzheimer's Association","keywords":"Connectome; Divergence (linguistics); Dementia; Similarity (geometry); Internal medicine; Medicine; Psychology; Statistics; Mathematics; Neuroscience; Artificial intelligence; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001092607,0.0003933301,0.0003898093,0.002185111,0.0002702173,0.0005548084,0.0003131853,0.0004338802,0.0009872904],"category_scores_gemma":[0.004000056,0.0001117624,0.0004437213,0.0007582927,0.0003612023,0.0005288041,0.0005673314,0.0003035554,0.0001444225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003544533,"about_ca_system_score_gemma":0.000227799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00174548,"about_ca_topic_score_gemma":0.002756376,"domain_scores_codex":[0.9996468,0.00009132187,0.00004319704,0.0001204624,0.00007057661,0.00002770837],"domain_scores_gemma":[0.9985393,0.0005164176,0.0004760494,0.0001402518,0.0001859616,0.0001420898],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004534233,0.00008833635,0.9636529,0.00004562847,0.0004236046,0.0001694668,0.0001377137,0.009646771,0.002606145,0.0003734478,0.0004387276,0.0219638],"study_design_scores_gemma":[0.00002517553,0.0002435336,0.8707358,0.00001799732,0.0001372874,0.0007250064,0.0001339043,0.1230852,0.001555796,0.002943264,0.0003613076,0.00003557395],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928243,0.0001756438,0.006037516,0.00004260219,0.000004950264,0.00002008012,0.0003707927,0.00003361877,0.0004903997],"genre_scores_gemma":[0.99822,0.00003478152,0.001280411,0.000005842129,0.000005190674,0.00001496451,0.0003426085,0.000002548876,0.00009353043],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002185111,"threshold_uncertainty_score":0.005778372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05289763998542495,"score_gpt":0.2973921677636944,"score_spread":0.2444945277782694,"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."}}