An open API service providing mapping between scientific papers and software projects that are mentioned in them.

Papers: 10.1371/journal.pone.0251800

https://doi.org/10.1371/journal.pone.0251800

Comparison of machine-learning methodologies for accurate diagnosis of sepsis using microarray gene expression data

Cited by: 5
Author(s): Dominik Schaack, Markus A. Weigand, Florian Uhle
Published: about 4 years ago

Software Mentions 5

bioconductor: limma
Linear Models for Microarray Data
Papers that mentioned: 7,776
Very Likely Science (78)
cran: keras
R Interface to 'Keras'
Papers that mentioned: 141
Very Likely Science (100)
cran: randomForest
Breiman and Cutler's Random Forests for Classification and Regression
Papers that mentioned: 1,447
Very Likely Science (100)
pypi: keras
Deep learning for humans.
Papers that mentioned: 141
Very Likely Science (90)
pypi: stats
Calculator-style statistical functions
Papers that mentioned: 3,105
Very Likely Science (90)