Artificial intelligence models in the surgical planning of low-grade gliomas: a systematic review
AI/ML models have shown promising results in diagnostic and management approaches for glioma resection. Nonetheless, this is based on a small number of studies (n=8) and remain preliminary. Validating the findings in external datasets with a larger patient population would help enhance the predictive capacity of the existing models.
Authors
- Atman Desai (ORCID: https://orcid.org/0000-0001-8387-3808)
- Vivek Sanker (ORCID: https://orcid.org/0000-0003-0615-8397)
- C.-G. Park
- Aparna Venkatesan (ORCID: https://orcid.org/0009-0005-2703-8695)
- Afia Salma
- David J. Park
- Zhikai Li
- Ajeya Sp
- Philip Heesen
Institutions
- University of Zurich (CH)
- Dow University of Health Sciences (PK)
- Indira Gandhi Medical College and Research Institute (IN)
- Government Medical College (IN)
- Addenbrooke's Hospital (GB)
- Stanford University (US)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2026-01-15
- DOI
- https://doi.org/10.3389/fonc.2025.1672289
- Primary Topic
- Glioma Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00