Published on in Vol 24, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27434, first published .
Improving Diabetes-Related Biomedical Literature Exploration in the Clinical Decision-making Process via Interactive Classification and Topic Discovery: Methodology Development Study

Improving Diabetes-Related Biomedical Literature Exploration in the Clinical Decision-making Process via Interactive Classification and Topic Discovery: Methodology Development Study

Improving Diabetes-Related Biomedical Literature Exploration in the Clinical Decision-making Process via Interactive Classification and Topic Discovery: Methodology Development Study

Adrian Ahne 1, 2, MSc;  Guy Fagherazzi 3, MSc, PhD;  Xavier Tannier 4, Prof Dr;  Thomas Czernichow 1, MSc, PhD;  Francisco Orchard 1, BSc

1 Epiconcept Company , Paris , FR

2 Exposome and Heredity team, Center of Epidemiology and Population Health, Hospital Gustave Roussy, Inserm, Paris-Saclay University, Villejuif , FR

3 Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, Luxembourg , LU

4 Laboratoire d’Informatique Medicale et d’Ingenierie des Connaissances pour la e-Sante, Limics, Inserm, University Sorbonne Paris Nord, Sorbonne University, Paris , FR

Corresponding Author:

  • Adrian Ahne, MSc
  • Exposome and Heredity team, Center of Epidemiology and Population Health, Hospital Gustave Roussy
  • Inserm
  • Paris-Saclay University
  • 20 Rue du Dr Pinel
  • Villejuif
  • FR
  • Phone: 33 142115386
  • Email: adrian.ahne@protonmail.com