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

Papers: 10.1371/journal.pone.0250787

https://doi.org/10.1371/journal.pone.0250787

A dynamic Bayesian network model for predicting organ failure associations without predefining outcomes

Cited by: 2
Author(s): R. A. De Blasi, Giuseppe Campagna, Stefano Finazzi
Published: about 4 years ago

Software Mentions 4

cran: bnlearn
Bayesian Network Structure Learning, Parameter Learning and Inference
Papers that mentioned: 113
Very Likely Science (85)
pypi: bnlearn
Python package for learning the graphical structure of Bayesian networks, parameter learning, inference and sampling methods.
Papers that mentioned: 113
Very Likely Science (90)
pypi: Clarify
A library for scraping and parsing election results from jurisdictions using Clarity elections systems.
Papers that mentioned: 16
Very Likely Science (65)
pypi: PACE
Data Quality of Experimental Data
Papers that mentioned: 13,779
Very Likely Science (90)