c(
person(given = c("Matthijs", "S."),
family = "Berends",
email = "m.berends@certe.nl",
role = c("aut", "cre"),
comment = c(ORCID = "0000-0001-7620-1800")),
person(given = c("Christian", "F."),
family = "Luz",
role = c("aut", "ctb"),
comment = c(ORCID = "0000-0001-5809-5995")),
person(given = "Dennis",
family = "Souverein",
role = c("aut", "ctb"),
comment = c(ORCID = "0000-0003-0455-0336")),
person(given = c("Erwin", "E.", "A."),
family = "Hassing",
role = c("aut", "ctb")),
person(given = c("Casper", "J."),
family = "Albers",
role = "ths",
comment = c(ORCID = "0000-0002-9213-6743")),
person(given = c("Judith", "M."),
family = "Fonville",
role = "ctb"),
person(given = c("Alex", "W."),
family = "Friedrich",
role = "ths",
comment = c(ORCID = "0000-0003-4881-038X")),
person(given = "Corinna",
family = "Glasner",
role = "ths",
comment = c(ORCID = "0000-0003-1241-1328")),
person(given = c("Eric", "H.", "L.", "C.", "M."),
family = "Hazenberg",
role = "ctb"),
person(given = "Gwen",
family = "Knight",
role = "ctb",
comment = c(ORCID = "0000-0002-7263-9896")),
person(given = "Annick",
family = "Lenglet",
role = "ctb",
comment = c(ORCID = "0000-0003-2013-8405")),
person(given = c("Bart", "C."),
family = "Meijer",
role = "ctb"),
person(given = "Sofia",
family = "Ny",
role = "ctb",
comment = c(ORCID = "0000-0002-2017-1363")),
person(given = c("Rogier", "P."),
family = "Schade",
role = "ctb"),
person(given = c("Bhanu", "N.", "M."),
family = "Sinha",
role = "ths",
comment = c(ORCID = "0000-0003-1634-0010")),
person(given = "Anthony",
family = "Underwood",
role = "ctb",
comment = c(ORCID = "0000-0002-8547-4277")))

Functions to simplify and standardise antimicrobial resistance (AMR)
data analysis and to work with microbial and antimicrobial properties by
using evidence-based methods, as described in <doi:10.18637/jss.v104.i03>.

Library to sample and clean text data, build N-gram model, Backoff algorithm etc.

Feedforward Artificial Neural Network optimized by Genetic
Algorithm
Francis Roy-Desrosiers, based on CUDAANN r6 project developed
by Emre Caglar.
This package provides a feedforward Artificial Neural
Network (ANN) optimized by Genetic Algorithm (GA).
Modifications in the Genetic algorithm from CUDAANN r6 have
been done to improve the speed, the convergence and the memory
management.