Comprehensive review of Bayesian network applications in gastrointestinal cancers

Table 3 Some popular Bayesian network software tools

Tools	Language	Description	Links
Bnlearn[26]	R	Python package for causal discovery by learning the graphical structure of Bayesian networks	http://www.bnlearn.com/
BNT[27]	MATLAB	Bayes net toolbox for Matlab	https://github.com/bayesnet/bnt
GOBNILP	C	Learning Bayesian network structure with integer programming	https://www.cs.york.ac.uk/aig/sw/gobnilp/
Bnstruct	R	Bnstruct is an R package which learns Bayesian networks from data with missing values	https://cran.r-project.org/web/packages/bnstruct
Bmmalone	C++	This project implements a number of algorithms for learning Bayesian network structures using state space search techniques.	https://github.com/bmmalone/urlearning-cpp
Causal-Learner[28]	MATLAB	A toolbox for causal structure and Markov blanket learning	https://github.com/z-dragonl/Causal-Learner
CausalFS[29]	C/C++	An open-source package of causal feature selection and causal (Bayesian network) structure learning	https://github.com/kuiy/CausalFS
Weka[30]	Java	Weka contains a collection of visualization tools and algorithms for data analysis and predictive modeling, together with graphical user interfaces for easy access to these functions	https://git.cms.waikato.ac.nz/weka/weka
Bene	C	An exact Bayesian network structure learning software based on dynamic programming	https://github.com/tomisilander/bene
Causal-learn	Python	Causal discovery in Python. It also includes (conditional) independence tests and score functions	https://github.com/py-why/causal-learn
pyCausalFS	Python	An open-source package of causal feature selection and causal (Bayesian network) structure learning	https://github.com/kuiy/pyCausalFS
CausalExplorer[31]	MATLAB	A MATLAB library of computational causal discovery and variable selection algorithms	https://github.com/mensxmachina/CausalExplorer
Pgmpy	Python	Python library for learning (structure and parameter), inference (probabilistic and causal), and simulations in Bayesian networks	https://github.com/pgmpy/pgmpy
Tetrad	Java	It provides algorithms the capability to discover causal models, search for models of latent structure	https://github.com/cmu-phil/tetrad
Causal discovery toolbox	Python	The causal discovery toolbox is a package for causal inference in graphs	https://github.com/FenTechSolutions/CausalDiscoveryToolbox
DoWhy[32]	Python	DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions	https://github.com/py-why/dowhy