# Comprehensive machine learning-based integration develops a novel prognostic model for glioblastoma

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/comprehensive-machine-learning-based-integration-develops-a-novel-prognostic/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Qian Jiang,Xiawei Yang,Teng Deng,Jun Yan,Fangzhou Guo,Ligen Mo,Seongha An,Qianrong Huang |
| Citations | 12 |
| DOI | 10.1016/j.omton.2024.200838 |
| Fields | Medicine |
| Open Access | true |
| OA Status | diamond |
| OA URL | https://doi.org/10.1016/j.omton.2024.200838 |
| OpenAlex ID | https://openalex.org/W4399793321 |
| PMID | 39072291 |
| Type | article |
| Year | 2024 |

## Paper authors

- [Teng Deng](https://scholariq.org/researchers/teng-deng/)

## Paper journal

- [Molecular Therapy Oncology](https://scholariq.org/journals/molecular-therapy-oncology/)

## Paper primary topic

- [Ferroptosis and cancer prognosis](https://scholariq.org/topics/ferroptosis-and-cancer-prognosis/)

## Paper topics

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

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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.