netDx: interpretable patient classification using integrated patient similarity networks
Abstract Patient classification has widespread biomedical and clinical applications, including diagnosis, prognosis, and treatment response prediction. A clinically useful prediction algorithm should be accurate, generalizable, be able to integrate diverse data types, and handle sparse data. A clini...
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| Autori principali: | , , , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Springer Nature
2019-03-01
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| Serie: | Molecular Systems Biology |
| Soggetti: | |
| Accesso online: | https://doi.org/10.15252/msb.20188497 |
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