Data-driven surgical decision-making – the prediction of resectability in patients with glioblastoma using machine learning

• J.M. Kernbach,
• G. Neuloh,
• J. Ort,
• K. Hakvoort,
• L. Dührsen,
• F.L. Ricklefs,
• S. Grau,
• H. Clusmann,
• D. Delev

Affiliations

J.M. Kernbach

RWTH Aachen University, Neurosurgical Artificial Intelligence Laboratory Aachen (NAILA), Aachen, Germany; RWTH Aachen University, Department of Neurosurgery, Faculty of Medicine, Aachen, Germany

G. Neuloh

RWTH Aachen University, Department of Neurosurgery, Faculty of Medicine, Aachen, Germany

J. Ort

RWTH Aachen University, Neurosurgical Artificial Intelligence Laboratory Aachen (NAILA), Aachen, Germany; RWTH Aachen University, Department of Neurosurgery, Faculty of Medicine, Aachen, Germany

K. Hakvoort

RWTH Aachen University, Neurosurgical Artificial Intelligence Laboratory Aachen (NAILA), Aachen, Germany; RWTH Aachen University, Department of Neurosurgery, Faculty of Medicine, Aachen, Germany

L. Dührsen

University Hospital Hamburg-Eppendorf, Department of Neurosurgery, Hamburg, Germany

F.L. Ricklefs

University Hospital Hamburg-Eppendorf, Department of Neurosurgery, Hamburg, Germany

S. Grau

University Hospital Köln, Department of Neurosurgery, Köln, Germany

H. Clusmann

RWTH Aachen University, Department of Neurosurgery, Faculty of Medicine, Aachen, Germany

D. Delev

RWTH Aachen University, Neurosurgical Artificial Intelligence Laboratory Aachen (NAILA), Aachen, Germany; RWTH Aachen University, Department of Neurosurgery, Faculty of Medicine, Aachen, Germany