{"paper":{"title":"An Uncertainty-Aware, Shareable and Transparent Neural Network Architecture for Brain-Age Modeling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["q-bio.PE"],"primary_cat":"cs.LG","authors_text":"Beate Endemann, Benjamin Risse, B\\\"orge Schmidt, Christian Gaser, Daniel Emden, Dominik Grotegerd, Fabian Bamberg, German National Cohort Study Center Consortium, Harald Kugel, Henry V\\\"olzke, James H. Cole, Jan Ernsting, Jochen G. Hirsch, Jonathan Repple, Kelvin Sarink, Klaus Berger, Lale Umutlu, Lukas Fisch, Marie Beisemann, Nils Opel, Nils R. Winter, Oyunbileg von Stackelberg, Ramona Felizitas Sowade, Ramona Leenings, Robin B\\\"ulow, Ronny Redlich, Susanne Meinert, Svenja Caspers, Thomas Kr\\\"oncke, Thoralf Niendorf, Tilo Kircher, Tim Hahn, Udo Dannlowski, Vincent Holstein","submitted_at":"2021-07-16T15:48:08Z","abstract_excerpt":"The deviation between chronological age and age predicted from neuroimaging data has been identified as a sensitive risk-marker of cross-disorder brain changes, growing into a cornerstone of biological age-research. However, Machine Learning models underlying the field do not consider uncertainty, thereby confounding results with training data density and variability. Also, existing models are commonly based on homogeneous training sets, often not independently validated, and cannot be shared due to data protection issues. Here, we introduce an uncertainty-aware, shareable, and transparent Mon"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.07977","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2107.07977/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}