Article

Identifying transcription patterns of histology and radiomics features in NSCLC with neural networks

2020-07-22

Abstract excerpt

<h4>Purpose</h4> To investigate the use of deep neural networks to learn associations between gene expression and radiomics or histology in non-small cell lung cancer (NSCLC). <h4>Materials and Methods</h4> Deep feedforward neural networks were used for radio-genomic mapping, where 21,766 gene expressions were inputs to individually predict histology and 101 CT radiomic features. Models were compared against log...

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Literature Corpus work: 1ad37885-f6d7-5c7e-ac40-2fa72c4e872d
DOI: 10.1101/2020.07.22.215558

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