A proof of concept of a machine learning algorithm to predict late-onset 21-hydroxylase deficiency in children with premature pubic hair - Sorbonne Université Access content directly
Journal Articles (Data Paper) Journal of Steroid Biochemistry and Molecular Biology Year : 2022

A proof of concept of a machine learning algorithm to predict late-onset 21-hydroxylase deficiency in children with premature pubic hair

Héléna Agnani
  • Function : Author
Guillaume Bachelot
  • Function : Author
Bettina Ribault
  • Function : Author
Jean Fiet
  • Function : Author
Yves Le Bouc
  • Function : Author
Irène Netchine
  • Function : Author
Muriel Houang
  • Function : Author
Antonin Lamazière

Dates and versions

hal-03972777 , version 1 (03-02-2023)

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Héléna Agnani, Guillaume Bachelot, Thibaut Eguether, Bettina Ribault, Jean Fiet, et al.. A proof of concept of a machine learning algorithm to predict late-onset 21-hydroxylase deficiency in children with premature pubic hair. Journal of Steroid Biochemistry and Molecular Biology, 2022, 220, pp.106085. ⟨10.1016/j.jsbmb.2022.106085⟩. ⟨hal-03972777⟩
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