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

Public (e)Health, Digital Epidemiology and Public Health Informatics (725) Natural Language Processing (693) New Methods (946) Ontologies, Classifications, and Coding (239) Attention Deficit Disorder (ADD/ADHD) (62) Data Science (271) Knowledge Translation and Implementation Science (399) Machine Learning (1471)

Published on in Vol 24, No 8 (2022): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/39888, first published .
Deciphering the Diversity of Mental Models in Neurodevelopmental Disorders: Knowledge Graph Representation of Public Data Using Natural Language Processing

Deciphering the Diversity of Mental Models in Neurodevelopmental Disorders: Knowledge Graph Representation of Public Data Using Natural Language Processing

Deciphering the Diversity of Mental Models in Neurodevelopmental Disorders: Knowledge Graph Representation of Public Data Using Natural Language Processing

Authors of this article:

Manpreet Kaur1 Author Orcid Image ;   Jeremy Costello2 Author Orcid Image ;   Elyse Willis1 Author Orcid Image ;   Karen Kelm1 Author Orcid Image ;   Marek Z Reformat2, 3 Author Orcid Image ;   Francois V Bolduc1, 4, 5, 6 Author Orcid Image
Article Authors Cited by (4) Tweetations (7) Metrics

Journals

  1. Dang L, Phan U, Nguyen N. GENA: A knowledge graph for nutrition and mental health. Journal of Biomedical Informatics 2023;145:104460 View
  2. Zhang W, Kong L, Lee S, Chen Y, Zhang G, Wang H, Song M. Detecting mental and physical disorders using multi-task learning equipped with knowledge graph attention network. Artificial Intelligence in Medicine 2024;149:102812 View
  3. Bourgeois A, Wendland J. Mental health disorder in preschool children: Do we have the best tools possible to detect it?. Neuropsychiatrie de l'Enfance et de l'Adolescence 2024;72(4):182 View