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Application of unsupervised analysis techniques to lung cancer patient data
This study applies unsupervised machine learning techniques for classification and clustering to a collection of descriptive variables from 10,442 lung cancer patient records in the Surveillance, Epidemiology, and End Results (SEER) program database. The goal is to automatically classify lung cancer...
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| Publicado no: | PLoS One |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Public Library of Science
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5598970/ https://ncbi.nlm.nih.gov/pubmed/28910336 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0184370 |
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