Back to search

Article

Small Patient Datasets Reveal Genetic Drivers of Non-Small Cell Lung Cancer Subtypes Using a Novel Machine Learning Approach

2021-07-29

Abstract excerpt

<h4>Background</h4> There are many small datasets of significant value in the medical space that are being underutilized. Due to the heterogeneity of complex disorders found in oncology, systems capable of discovering patient subpopulations while elucidating etiologies is of great value as it can indicate leads for innovative drug discovery and development. <h4>Materials and Methods</h4> Here, we report on a machi...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
af8d4dbb-d6b2-5c6b-8bb9-8aaf5b74e63f
DOI
10.1101/2021.07.27.21261075
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Small Patient Datasets Reveal Genetic Drivers of Non-Small Cell Lung Cancer Subtypes Using a Novel Machine Learning ApproachDOI 10.1101/2021.07.27.21261075
Select a neighboring publication to make it the new centre.