{"paper":{"title":"Atlas: A Novel Pathology Foundation Model by Mayo Clinic, Charit\\'e, and Aignostics","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CV","authors_text":"Alexander M\\\"ollers, Alexandra Carpen-Amarie, Andreas Kunft, Andrew Norgan, Beatriz Perez Cancer, David Horst, Edwin de Jong, Frederick Klauschen, Gabriel Dernbach, Gavin Schaeferle, Helmut Hoffer von Ankershoffen, Jonas Dippel, Kai Standvoss, Klaus-Robert M\\\"uller, Lukas Ruff, Matt Redlon, Maximilian Alber, Moritz Kr\\\"ugener, Neelay Shah, Panos Korfiatis, Patrick Duffy, Philipp Jurmeister, Philipp Seegerer, Simon Schallenberg, Stephan Tietz, Timo Milbich, Timoth\\'ee Lesort","submitted_at":"2025-01-09T18:06:45Z","abstract_excerpt":"Recent advances in digital pathology have demonstrated the effectiveness of foundation models across diverse applications. In this report, we present Atlas, a novel vision foundation model based on the RudolfV approach. Our model was trained on a dataset comprising 1.2 million histopathology whole slide images, collected from two medical institutions: Mayo Clinic and Charit\\'e - Universt\\\"atsmedizin Berlin. Comprehensive evaluations show that Atlas achieves state-of-the-art performance across twenty-one public benchmark datasets, even though it is neither the largest model by parameter count n"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.05409","kind":"arxiv","version":2},"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/2501.05409/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"}