{"id":"W2911963582","doi":"10.1155/2019/9507193","title":"Cloud-Based Brain Magnetic Resonance Image Segmentation and Parcellation System for Individualized Prediction of Cognitive Worsening","year":2019,"lang":"en","type":"article","venue":"Journal of Healthcare Engineering","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; H. Lundbeck A/S; Servier; Eisai; Elan; Northern California Institute for Research and Education; Johns Hopkins University; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Merck; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Alzheimer's Drug Discovery Foundation; National Institute of Neurological Disorders and Stroke; IXICO; Takeda Pharmaceutical Company; AbbVie; Alzheimer's Association; Foundation for the National Institutes of Health; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics","keywords":"Dementia; Segmentation; Neuroimaging; Receiver operating characteristic; Magnetic resonance imaging; Cognitive decline; Cognition; Artificial intelligence; Computer science; Machine learning; Medicine; Radiology; Disease; Pathology; Psychiatry","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":[],"consensus_categories":[],"category_scores_codex":[0.0007293094,0.00008167337,0.0002400119,0.0002407172,0.00002728515,0.00001316051,0.00002388547,0.0000469423,0.00001208264],"category_scores_gemma":[0.0001971196,0.00007548813,0.00005903052,0.000131796,0.00001313269,0.000102309,0.000008115689,0.0001506234,6.536383e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000923039,"about_ca_system_score_gemma":0.0001066221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007717152,"about_ca_topic_score_gemma":5.902402e-7,"domain_scores_codex":[0.9989414,0.00005495918,0.0004186708,0.00009745502,0.0003314399,0.0001561156],"domain_scores_gemma":[0.9988598,0.0003473253,0.0002020605,0.00004514507,0.0004508519,0.00009478704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005760203,0.0002100438,0.6306309,0.01569253,0.0002146934,0.00006067026,0.00240036,0.0005161325,0.2323755,0.0002043868,0.0001584458,0.1117762],"study_design_scores_gemma":[0.01985831,0.009855281,0.8155834,0.0112619,0.000277733,0.0002429592,0.004310015,0.06292916,0.07487263,0.00001493181,0.0006027473,0.0001909113],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9754916,0.001517906,0.02143841,0.0004796737,0.0001984873,0.0008014459,0.00003309975,0.00001370803,0.00002567187],"genre_scores_gemma":[0.9952218,0.00003590344,0.004499504,0.00003873275,0.0001229902,0.00001441814,0.00002096546,0.0000153838,0.00003029364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1849526,"threshold_uncertainty_score":0.3078316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01300100579314469,"score_gpt":0.2983763816213805,"score_spread":0.2853753758282359,"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."}}