# Application of artificial intelligence in forecasting survival in high-grade glioma: systematic review and meta-analysis involving 79,638 participants

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/application-of-artificial-intelligence-in-forecasting-survival-in-high-grade/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Ibrahim Mohammadzadeh,Bardia Hajikarimloo,Behnaz Niroomand,Pooya Eini,Ramin Ghanbarnia,Mohammad Amin Habibi,Abdulrahman Albakr,Hamid Borghei-Razavi |
| Citations | 23 |
| DOI | 10.1007/s10143-025-03419-y |
| Fields | Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4407594802 |
| PMID | 39954167 |
| Type | review |
| Year | 2025 |

## Paper authors

- [Abdulrahman Albakr](https://scholariq.org/researchers/abdulrahman-albakr/)

## Paper journal

- [Neurosurgical Review](https://scholariq.org/journals/neurosurgical-review/)

## Paper primary topic

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)

## Paper topics

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [Glioma Diagnosis and Treatment](https://scholariq.org/topics/glioma-diagnosis-and-treatment/)
- [MRI in cancer diagnosis](https://scholariq.org/topics/mri-in-cancer-diagnosis/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.