# Gene expression–based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/gene-expression-based-survival-prediction-in-lung-adenocarcinoma-a-multi-site/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Kerby Shedden,Jeremy M. G. Taylor,David E. Misek,Andrew C. Chang,Samir Hanash,Rork Kuick,David G. Beer,Steven A. Enkemann,Timothy J. Yeatman,Steven A. Eschrich,Michael E. Gruidl,Anupama Sharma,Tsao Ml,Igor Jurišica,Chang‐Qi Zhu,Daniel Strumpf,Frances A. Shepherd,William L. Gerald,János Szőke,Maureen F. Zakowski,Valerie W. Rusch,Mark G. Kris,Agnès Viale,Noriko Motoi,William D. Travis,Thomas J. Giordano,Keyue Ding,Lesley Seymour,Katsuhiko Naoki,Nathan A. Pennell,Barbara A. Weir,Roel Verhaak,M. Meyerson,Christine Ladd‐Acosta,Todd R. Golub,Barbara Conley,Venkatraman Seshan,Kevin K. Dobbin,Tracy Lively,James W. Jacobson |
| Citations | 1,246 |
| DOI | 10.1038/nm.1790 |
| Fields | Biochemistry, Genetics and Molecular Biology,Medicine |
| Open Access | true |
| OA Status | green |
| OA URL | https://www.ncbi.nlm.nih.gov/pmc/articles/2667337 |
| OpenAlex ID | https://openalex.org/W2132165198 |
| PMID | 18641660 |
| Type | article |
| Year | 2008 |

## Paper authors

- [Frances A. Shepherd](https://scholariq.org/researchers/frances-a-shepherd/)
- [Mark G. Kris](https://scholariq.org/researchers/mark-g-kris/)

## Paper journal

- [Nature Medicine](https://scholariq.org/journals/nature-medicine/)

## Paper primary topic

- [Lung Cancer Treatments and Mutations](https://scholariq.org/topics/lung-cancer-treatments-and-mutations/)

## Paper topics

- [Lung Cancer Treatments and Mutations](https://scholariq.org/topics/lung-cancer-treatments-and-mutations/)
- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [Gene expression and cancer classification](https://scholariq.org/topics/gene-expression-and-cancer-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.