Updates on glioblastoma multiforme: From epidemiology to imaging and artificial intelligence

doi:10.35711/aimi.v6.i2.108032

Advanced Search

BPG is committed to discovery and dissemination of knowledge

Home / Archive / Volume 6, Issue 2

This Article

Academic Content and Language Evaluation of This Article

CrossCheck and Google Search of This Article

Academic Rules and Norms of This Article

Citation of this article

Corresponding Author of This Article

Research Domain of This Article

Article-Type of This Article

Open-Access Policy of This Article

Times Cited Counts in Google of This Article

Number of Hits and Downloads for This Article

Total Article Views (12)

All Articles published online

The chart showing PDF series, HTML series, Figures (1-2) series, Tables (1-3) series.

Item

Count

PDF

HTML

Figures (1-2)

Tables (1-3)

Sum=12

Sep 8, 2025 (publication date) through Sep 3, 2025

Times Cited of This Article

Times Cited (0)

Journal Information of This Article

Publication Name

Artificial Intelligence in Medical Imaging

ISSN

2644-3260

Publisher of This Article

Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Review

Artif Intell Med Imaging. Sep 8, 2025; 6(2): 108032
Published online Sep 8, 2025. doi: 10.35711/aimi.v6.i2.108032

Updates on glioblastoma multiforme: From epidemiology to imaging and artificial intelligence

M'hamed Bentourkia, Redha-Alla Abdo

M'hamed Bentourkia, Redha-Alla Abdo, Department of Medical Imaging and Radiation Sciences, University of Sherbrooke, Sherbrooke J1H5N4, Quebec, Canada

Author contributions: Bentourkia M designed the study; Abdo RA wrote the first draft, and both authors revised the review manuscript.

Conflict-of-interest statement: All authors state that they have no conflicts of interest to report.

Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/

Corresponding author: M'hamed Bentourkia, PhD, Professor, Department of Medical Imaging and Radiation Sciences, University of Sherbrooke, 3001, 12th Avenue North, Sherbrooke J1H5N4, Quebec, Canada. mhamed.bentourkia@usherbrooke.ca

Received: April 3, 2025
Revised: May 12, 2025
Accepted: August 12, 2025
Published online: September 8, 2025
Processing time: 153 Days and 5.7 Hours

Core Tip

Core Tip: Glioblastoma remains one of the most lethal brain cancers due to its complexity and resistance to therapy. Artificial intelligence (AI) offers transformative potential in early detection, precision surgery, personalized treatment, and drug discovery. By integrating imaging, genomics, and clinical data, AI paves the way to improved capabilities for faster and more effective glioblastoma care.