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This work is supported by grant PDC2023-145812-I00 (Project SAMPL2D), which is funded by MI- CIU/AEI/10.13039/501100011033 and by "Next Generation EU /PRTR".

Analysis of institutional authors

Casanova-Carvajal, OscarAuthor

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May 13, 2025
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A Review of Artificial Intelligence-Based Systems for Non-Invasive Glioblastoma Diagnosis

Publicated to:Life. 15 (4): 643- - 2025-04-14 15(4), DOI: 10.3390/life15040643

Authors: Contreras, Kebin; Velez-Varela, Patricia E; Casanova-Carvajal, Oscar; Alvarez, Angel Luis; Urbano-Bojorge, Ana Lorena

Affiliations

Univ Cauca, Fac Ciencias Nat Exactas & Educ FACNED, Dept Biol, Popayan 190002, Colombia - Author
Univ Politecn Madrid, Ctr Tecnol Biomed, Campus Montegancedo, Madrid 28040, Spain - Author
Univ Politecn Madrid, Escuela Tecn Super Ingn & Diseno Ind ETSIDI, Dept Electr Elect Automat & Fis Aplicada, Madrid 28040, Spain - Author
Univ Rey Juan Carlos, Escuela Ingn Fuenlabrada, Madrid 28922, Spain - Author

Abstract

Background: Glioblastoma multiforme (GBM) is an aggressive brain tumor with a poor prognosis. Traditional diagnosis relies on invasive biopsies, which pose surgical risks. Advances in artificial intelligence (AI) and machine learning (ML) have improved non-invasive GBM diagnosis using magnetic resonance imaging (MRI), offering potential advantages in accuracy and efficiency. Objective: This review aims to identify the methodologies and technologies employed in AI-based GBM diagnostics. It further evaluates the performance of AI models using standard metrics, highlighting both their strengths and limitations. Methodology: In accordance with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, a systematic review was conducted across major academic databases. A total of 104 articles were identified in the initial search, and 15 studies were selected for final analysis after applying inclusion and exclusion criteria. Outcomes: The included studies indicated that the signal T1-weighted imaging (T1WI) is the most frequently used MRI modality in AI-based GBM diagnostics. Multimodal approaches integrating T1WI with diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) have demonstrated improved classification performance. Additionally, AI models have shown potential in surpassing conventional diagnostic methods, enabling automated tumor classification and enhancing prognostic predictions.

Keywords

Deep learningFeatureGlioblastomaMachine learningMagnetic resonance imagingPrecision medicinPrecision medicineResectionTumors

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Life due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2025, it was in position 22/107, thus managing to position itself as a Q1 (Primer Cuartil), in the category Biology.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2025-08-21:

  • Scopus: 1

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-08-21:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 5 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

    Leadership analysis of institutional authors

    This work has been carried out with international collaboration, specifically with researchers from: Colombia.