Deciphering the Diversity of Mental Models in Neurodevelopmental Disorders: Knowledge Graph Representation of Public Data Using Natural Language Processing.
Manpreet KaurJeremy CostelloElyse WillisKaren KelmMarek Z ReformatFrancois V BolducPublished in: Journal of medical Internet research (2022)
We show for the first time that generating KGs from web-based data can capture the complex needs of families dealing with ADHD or ASD. Moreover, we showed points of convergence between families and health professionals' KGs. Natural language processing-based KG provides access to a large sample size, which is often a limiting factor for traditional in-person mental model mapping. Our work offers a high throughput access to mental model maps, which could be used for further in-person validation, knowledge mobilization projects, and basis for communication about potential blind spots from stakeholders in interactions about NDDs. Future research will be needed to identify how concepts could interact together differently for each stakeholder.
Keyphrases
- autism spectrum disorder
- mental health
- healthcare
- high throughput
- attention deficit hyperactivity disorder
- electronic health record
- big data
- intellectual disability
- high resolution
- working memory
- quality improvement
- emergency department
- convolutional neural network
- single cell
- artificial intelligence
- deep learning
- human health