{"id":"W3150896365","doi":"10.3390/s21072427","title":"Combined Atlas and Convolutional Neural Network-Based Segmentation of the Hippocampus from MRI According to the ADNI Harmonized Protocol","year":2021,"lang":"en","type":"article","venue":"Sensors","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre; University of Calgary","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Servier; Eisai; Northern California Institute for Research and Education; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Avid Radiopharmaceuticals; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health; Heart and Stroke Foundation of Canada","keywords":"Convolutional neural network; Computer science; Protocol (science); Artificial intelligence; Atlas (anatomy); Segmentation; Pattern recognition (psychology); Data mining; Medicine; Pathology; Anatomy","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":[0.002217014,0.001361307,0.0007376457,0.001825743,0.0007890678,0.001242829,0.001681246,0.001154835,0.002020928],"category_scores_gemma":[0.004290082,0.0006074228,0.0009913996,0.001168389,0.0006904181,0.001115904,0.001517488,0.001090691,0.001238816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001067722,"about_ca_system_score_gemma":0.002784445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009710044,"about_ca_topic_score_gemma":0.0196791,"domain_scores_codex":[0.9987769,0.0002149474,0.000163453,0.0004161776,0.0003421951,0.00008638945],"domain_scores_gemma":[0.9988238,0.0001781972,0.0001582567,0.000358785,0.0004347348,0.00004615909],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001325397,0.0003418011,0.01849726,0.001438735,0.0009937921,0.0008317551,0.0008326638,0.06367612,0.180021,0.007859739,0.02358887,0.7005929],"study_design_scores_gemma":[0.000259537,0.0009402859,0.04874484,0.0004067229,0.0008753582,0.005824257,0.0004346318,0.5978239,0.2744037,0.01536923,0.05456145,0.0003560845],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1128142,0.002206004,0.8626357,0.0003762814,0.0002654377,0.001716211,0.004093091,0.01091735,0.004975649],"genre_scores_gemma":[0.2540244,0.001176176,0.7263565,0.0003775055,0.00006772213,0.00153966,0.01033792,0.001321968,0.004798231],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009710044,"threshold_uncertainty_score":0.01930708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03235015929178652,"score_gpt":0.2744477638356134,"score_spread":0.2420976045438269,"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."}}