Machine learning in clinical and epidemiological research: isn't it time for biostatisticians to work on it?

Authors

  • Danila Azzolina University of Piemonte Orientale
  • Ileana Baldi (University of Padova) University of Padova
  • Giulia Barbati University of Trieste
  • Paola Berchialla University of Torino
  • Daniele Bottigliengo University of Padova
  • Andrea Bucci Marche Polytechnic University
  • Stefano Calza University of Brescia
  • Pasquale Dolce University of Napoli Federico II
  • Valeria Edefonti University of Milan
  • Andrea Faragalli ( Marche Polytechnic University
  • Giovanni Fiorito University of Sassari
  • Ilaria Gandin Area Science Park, Trieste
  • Fabiola Giudici University of Padova
  • Dario Gregori University of Padova
  • Caterina Gregorio University of Padova
  • Francesca Ieva Polytechnic of Milano
  • Corrado Lanera University of Padova
  • Giulia Lorenzoni University of Padova
  • Michele Marchioni University of Chieti-Pescara
  • Alberto Milanese University of Rome, La Sapienza
  • Andrea Ricotti University of Torino
  • Veronica Sciannameo University of Padova
  • Giuliana Solinas University of Sassari
  • Marika Vezzoli University of Brescia

DOI:

https://doi.org/10.2427/13245

Abstract

In recent years, there has been a widespread cross-fertilization between Medical Statistics and Machine Learning (ML) techniques.

Downloads

Published

2022-01-27

Issue

Vol. 16 No. 4 (2019)

Section

Editorial

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.