# Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/imaging-patterns-predict-patient-survival-and-molecular-subtype-in-glioblastoma/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Luke Macyszyn,Hamed Akbari,Jared Pisapia,Xiao Da,Mark Attiah,Vadim Pigrish,Yingtao Bi,Sharmistha Pal,Ramana V. Davuluri,Laura Roccograndi,Nadia Dahmane,Maria Martinez‐Lage,George Biros,Ronald L. Wolf,Michel Bilello,Donald M. O’Rourke,Christos Davatzikos |
| Citations | 311 |
| DOI | 10.1093/neuonc/nov127 |
| Fields | Medicine,Neuroscience |
| Open Access | true |
| OA Status | bronze |
| OA URL | https://academic.oup.com/neuro-oncology/article-pdf/18/3/417/7640370/nov127.pdf |
| OpenAlex ID | https://openalex.org/W2221563957 |
| PMID | 26188015 |
| Type | article |
| Year | 2015 |

## Paper authors

- [Luke Macyszyn](https://scholariq.org/researchers/luke-macyszyn/)

## Paper primary topic

- [Glioma Diagnosis and Treatment](https://scholariq.org/topics/glioma-diagnosis-and-treatment/)

## Paper topics

- [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/)
- [Brain Tumor Detection and Classification](https://scholariq.org/topics/brain-tumor-detection-and-classification/)

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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.