Publications by authors named "Hannah Dyson"
Diffuse gliomas are incurable brain tumors, yet there is significant heterogeneity in patient survival. Advanced computational techniques such as radiomics show potential for presurgical prediction of survival and other outcomes from neuroimaging. However, these techniques ignore non-lesioned brain features that could be essential for improving prediction accuracy.
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- Gliomas are the most prevalent malignant brain tumors, and identifying mutations in the IDH gene can significantly improve patient survival and quality of life.
- This study explored a new method to non-invasively predict IDH status using connectomics from standard MRI scans of 234 adult patients, applying various machine learning models.
- The results highlighted that the random forest model outperformed others in predicting IDH status, supporting connectomics as a promising technique for understanding tumor genetics and brain network interactions.
Effectiveness of a small-group vocabulary intervention programme: evidence from a regression discontinuity design.
Int J Lang Commun Disord
September 2018
Background: Children's vocabulary knowledge is closely related to other measures of language development and to literacy skills and educational attainment.
Aim: To use a regression discontinuity design (RDD) to evaluate the effectiveness of a small-group vocabulary intervention programme for children with poor vocabulary knowledge.
Methods & Procedures: The vocabulary knowledge of children (N = 199) aged 6-9 years was assessed in six classes.