Article

Sparse input neural networks to differentiate 32 primary cancer types based on somatic point mutations

2020-05-15

Abstract excerpt

This paper aims to differentiate cancer types from primary tumour samples based on somatic point mutations (SPM). Primary cancer site identification is necessary to perform site-specific and potentially targeted treatment. Current methods like histopathology/lab-tests cannot accurately determine cancers origin, which results in empirical patient treatment and poor survival rates. The availability of large deoxyrib...

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Literature Corpus work: ce56dfd8-2f1d-523c-a926-2b67e5785b85
DOI: 10.1101/2020.05.13.092916

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