Enhancing decision-making in glioblastoma surgery through an explainable human-AI collaboration: an international multicenter model development and external validation study

Abstract Surgical resection improves survival in glioblastoma, yet predicting the extent of resection (EOR) remains highly challenging. We developed and externally validated an explainable AI model to generate personalized EOR estimates in 811 glioblastoma patients undergoing microsurgical resection...

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Bibliografische Detailangaben

Hauptverfasser:	Julius M. Kernbach, Urte Schroeder, Karlijn Hakvoort, Jonas Ort, Hussam Hamou, Danilo Bzdok, Yasin Temel, Pieter Kubben, Charlotte Weyland, Martin Wiesmann, Victor Staartjes, Kevin Akeret, Moira Vieli, Carlo Serra, Luca Regli, Stefan Grau, Lasse Dührsen, Franz Ricklefs, Oliver Schnell, David Ryan Ormond, Alexander Grote, Matthias Simon, Hagen Meredig, Marianne Schell, Martin Bendszus, Georg Neuloh, Hans Clusmann, Dieter-Henrik Heiland, Daniel Delev
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Nature Portfolio 2025-11-01
Schriftenreihe:	npj Precision Oncology
Online-Zugang:	https://doi.org/10.1038/s41698-025-01183-2
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