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Schwiete Foundation Mannheim"},{"DOI":"10.13039\/501100003042","name":"Else Kr\u00f6ner-Fresenius-Stiftung","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003042","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Dieter Schwarz Stiftung"},{"DOI":"10.13039\/501100007311","name":"Deutsche Kinderkrebsstiftung","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100007311","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007158","name":"Fondazione Ricerca Molinette","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100007158","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001711","name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001711","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["SFB 1389"],"award-info":[{"award-number":["SFB 1389"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Nat Cancer"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Molecular testing is essential for classifying central nervous system (CNS) tumors, with methylation profiling providing the highest diagnostic granularity. However, this requires more resources and time than conventional hematoxylin and eosin (H&amp;E) histopathology, which is widely available globally. Here we propose Hetairos, an artificial intelligence algorithm that predicts 102 methylation-based CNS tumor subtypes from digital H&amp;E slides. Built and validated on 9,606 patients and over 11,000 slides from 11 centers across four continents, Hetairos identified 50\u201370% of cases with high confidence, achieving an accuracy of 0.87 for its highest-rated predictions. Hetairos outperformed five board-certified neuropathologists in a direct histology-only comparison (0.68 versus 0.30). Prospective evaluation in routine diagnostics confirmed its performance, reducing turnaround time from 12 days (molecular testing) to 12\u2009min. Hetairos supports diagnostic decision-making across the full spectrum of pediatric and adult CNS tumors by narrowing differential diagnoses and guiding efficient testing.<\/jats:p>","DOI":"10.1038\/s43018-026-01186-3","type":"journal-article","created":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T09:03:25Z","timestamp":1781082205000},"page":"884-898","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Hetairos is a histology-based artificial intelligence model for predicting central nervous system tumor methylation subtypes"],"prefix":"10.1038","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1784-8844","authenticated-orcid":false,"given":"Darui","family":"Jin","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2184-0856","authenticated-orcid":false,"given":"Artem","family":"Shmatko","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Areeba","family":"Patel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-2911-5708","authenticated-orcid":false,"given":"Samuel","family":"Rutz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7821-0282","authenticated-orcid":false,"given":"Lukas","family":"Friedrich","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9999-576X","authenticated-orcid":false,"given":"Rouzbeh","family":"Banan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ramin","family":"Rahmanzade","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3237-6021","authenticated-orcid":false,"given":"Philipp","family":"Sievers","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefan","family":"Hamelmann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Schrimpf","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-2117-6381","authenticated-orcid":false,"given":"Kirsten","family":"G\u00f6bel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Henri","family":"Bogumil","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8745-4405","authenticated-orcid":false,"given":"Sybren L. 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