Investigating heterogeneity across autism, ADHD, and typical development using measures of cortical thickness, surface area, cortical/subcortical volume, and structural covariance.
Frontiers in child and adolescent psychiatry, ISSN: 2813-4540, Vol: 2, Page: 1171337
2023
- 4Citations
- 10Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations4
- Citation Indexes4
- CrossRef4
- Captures10
- Readers10
- 10
Article Description
Attention-deficit/hyperactivity disorder (ADHD) and autism are multi-faceted neurodevelopmental conditions with limited biological markers. The clinical diagnoses of autism and ADHD are based on behavioural assessments and may not predict long-term outcomes or response to interventions and supports. To address this gap, data-driven methods can be used to discover groups of individuals with shared biological patterns.
Bibliographic Details
http://www.ncbi.nlm.nih.gov/pubmed/39839588; http://dx.doi.org/10.3389/frcha.2023.1171337; https://www.frontiersin.org/articles/10.3389/frcha.2023.1171337/full; https://dx.doi.org/10.3389/frcha.2023.1171337; https://www.frontiersin.org/journals/child-and-adolescent-psychiatry/articles/10.3389/frcha.2023.1171337/full
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