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

Public (e)Health, Digital Epidemiology and Public Health Informatics (1008) Natural Language Processing (917) New Methods (1134) Ontologies, Classifications, and Coding (324) Attention Deficit Disorder (ADD/ADHD) (90) Data Science (357) Knowledge Translation and Implementation Science (513) Machine Learning (2076)

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 (7) 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
  4. HOY T, BILAL I, LIOU Z. Grounded Models: The Future of Sensemaking in a World of Generative AI. Ethnographic Praxis in Industry Conference Proceedings 2023;2023(1):159 View
  5. Taha M, Abdelwahab S, Aljahdali I, Oraibi O, Oraibi B, Alfaifi H, Alzahrani A, Farasani A, Jerah A, Babiker Y. Unveiling the dynamic landscape of artificial intelligence in attention-deficit/hyperactivity disorder (ADHD) research: a comprehensive analysis of trends, intellectual structure, and thematic evolution. Current Psychology 2025;44(9):8068 View

Conference Proceedings

  1. Pandey S, Sharma S. 2023 6th International Conference on Information Systems and Computer Networks (ISCON). ML Algorithms that have been Utilised to Classify Neuro-Developmental Disorders: A Review View
  2. Pandey S, Sharma S, Agarwal A. 2024 4th International Conference on Advancement in Electronics & Communication Engineering (AECE). ML based Pre-Diagnosis Framework for early detection of Neurodevelopmental Disorders View