# Artificial intelligence-based tools for precision diagnosis and treatment of neurofibromatosis type 1 associated peripheral and central glial tumors

## TL;DR

This paper explores how AI can help diagnose and treat glial tumors linked to Neurofibromatosis Type 1, a hereditary condition that increases cancer risk.

## Contribution

The paper reviews AI applications and publicly available datasets for Neurofibromatosis Type 1-associated glial tumors.

## Key findings

- AI methods show promise in understanding tumor development and personalizing treatment strategies.
- A review of publicly available datasets highlights current resources for research in this area.
- Future challenges in AI application for Neurofibromatosis Type 1 are discussed to guide further research.

## Abstract

Modern Artificial Intelligence (AI) has demonstrated its effectiveness by achieving human-level performance in various complex tasks, including the biomedical field. Cancer research, adapting to a fast-changing world, is leveraging AI as a promising framework to better understand tumor development. Moreover, current AI methods can help predict more suitable and personalized treatment strategies for specific types of tumors. We explored AI methods applied to Neurofibromatosis Type 1, focusing on glial tumors. Additionally, we have reviewed all publicly available datasets to date. Discussion of future challenges is highly desirable since Neurofibromatosis Type 1 is one of the most common hereditary tumor syndromes and is associated with an increased rate of glial tumors as well as a reduced life expectancy due to malignancy.