Artificial intelligence models in the surgical planning of low-grade gliomas: a systematic review.

ABSTRACT:

Introduction

AI techniques like convolutional neural networks (CNN), deep learning (DL), and neural networks (NN) have made it easier to automatically extract important clinical data for glioma post-treatment monitoring and surgical planning.

Objective

To systematically review and analyze the role of AI/ML models in the surgical planning of LGG.

Methodology

A rigorous and comprehensive systematic literature search was conducted across PubMed, Scopus, Web of Science Advance, ArXiV, and Embase (Ovid) databases from inception to July 14, 2025. Articles related to the utility of ML models in the surgical planning of LGG were included.

Results

Our review included eight studies in both preoperative and intraoperative settings with variation in the type of AI applied,

SUBMITTER: Sanker V 

PROVIDER: S-EPMC12851994 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature