This paper is in the following e-collection/theme issue:

Clinical Information and Decision Making (1423) Decision Support for Health Professionals (1200) Natural Language Processing (700) Machine Learning (1486) Diabetes (191) Ontologies, Classifications, and Coding (239) Information Retrieval (294)

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

Authors of this article:

Adrian Ahne1, 2 Author Orcid Image ;   Guy Fagherazzi3 Author Orcid Image ;   Xavier Tannier4 Author Orcid Image ;   Thomas Czernichow2 Author Orcid Image ;   Francisco Orchard2 Author Orcid Image
Article Authors Cited by (5) Tweetations (16) Metrics

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

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

2 Epiconcept Company, Paris, France

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

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

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, 94800
  • France
  • Phone: 33 142115386
  • Email: adrian.ahne@protonmail.com