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01-12-2024 | Glioblastoma | Correspondence

The implications of machine learning in predicting glioblastoma recurrence: a correspondence

Authors: Samuel Berchi Kankam, Mohamed Jalloh

Published in: Neurosurgical Review | Issue 1/2024

Excerpt

Glioblastoma (GBM) stands as one of the most aggressive brain cancers, characterized by its rapid growth and high recurrence rate [1]. The prognosis for GBM patients is notoriously poor, with median survival times hovering around 15 months despite current treatment modalities [2, 3]. One of the primary challenges in GBM management is accurately predicting tumor recurrence and patient mortality, which are crucial for personalizing treatment plans and improving outcomes. In this context, machine learning (ML) algorithms have emerged as a promising tool, offering new insights and methodologies for tackling this formidable challenge [4]. …

Kankam SB (2024) Racial disparities and glioblastoma recurrence; a double impact for increased patient mortality: a correspondence. Neurosurg Rev 47(1):82CrossRefPubMed

Jalloh M, Kankam SB Harnessing imaging biomarkers for glioblastoma metastasis diagnosis: a correspondence. J Neuro-Oncology 2024 Feb 23:1–3

Shafizadeh M, Farzaneh F, Kankam SB, Jangholi E, Shafizadeh Y, Khoshnevisan A (2023) Effects of postoperative intravenous cyclosporine treatment on the survival and functional performance status of patients with glioblastoma: a randomized, triple-blinded, placebo-controlled clinical trial. World Neurosurg 176:e548–e556CrossRefPubMed

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Title: The implications of machine learning in predicting glioblastoma recurrence: a correspondence
Authors: Samuel Berchi Kankam
Mohamed Jalloh
Publication date: 01-12-2024
Publisher: Springer Berlin Heidelberg
Keywords: Glioblastoma
Glioblastoma
Glioblastoma
Magnetic Resonance Imaging
Magnetic Resonance Imaging
Published in: Neurosurgical Review / Issue 1/2024
Print ISSN: 0344-5607
Electronic ISSN: 1437-2320
DOI: https://doi.org/10.1007/s10143-024-02403-2

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The implications of machine learning in predicting glioblastoma recurrence: a correspondence

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