{"id":"W4311330992","doi":"10.3389/fneur.2022.979774","title":"Multimodal brain age prediction fusing morphometric and imaging data and association with cardiovascular risk factors","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Children's Hospital; Hotchkiss Brain Institute; University of Calgary","funders":"Canadian Open Neuroscience Platform; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Convolutional neural network; Magnetic resonance imaging; Human brain; Artificial intelligence; Neuroimaging; Functional magnetic resonance imaging; Computer science; Pattern recognition (psychology); Medicine; Psychology; Neuroscience; Radiology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009326871,0.0006215634,0.0005452548,0.001736354,0.0001151687,0.0005120609,0.0002431056,0.000512076,0.0009590476],"category_scores_gemma":[0.002888326,0.0001521753,0.0004029972,0.0006566634,0.0001461044,0.0004230004,0.0004564062,0.0002960006,0.0002797735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001662382,"about_ca_system_score_gemma":0.0001917208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003310713,"about_ca_topic_score_gemma":0.00365567,"domain_scores_codex":[0.9997979,0.00005281946,0.00001375469,0.00007585559,0.00002936763,0.00003045845],"domain_scores_gemma":[0.9992042,0.0002943416,0.0002070845,0.00007846717,0.000153487,0.00006229716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001645482,0.00031162,0.815073,0.0001963251,0.0005759761,0.0004320146,0.0002473326,0.02320435,0.01787611,0.0003793091,0.001722901,0.1383355],"study_design_scores_gemma":[0.00001981473,0.0004044456,0.738437,0.0000780136,0.000350367,0.001041292,0.0001818851,0.2503712,0.006509304,0.001448449,0.001096226,0.0000620343],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9864321,0.0008048379,0.01071568,0.00009137127,0.00002445036,0.00001737319,0.001154935,0.0001160688,0.0006431277],"genre_scores_gemma":[0.9939005,0.0002024925,0.004724008,0.00001460527,0.00003237736,0.00001375062,0.0008438643,0.000008975643,0.0002594558],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003310713,"threshold_uncertainty_score":0.006582856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01771749259483036,"score_gpt":0.2135192851662288,"score_spread":0.1958017925713984,"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."}}