22 citations · 22 across the 4 of their papers we have counts for
4 papers
Random Forest regression for manifold-valued responses
Dimosthenis Tsagkrasoulis, Giovanni Montana
An increasing array of biomedical and computer vision applications requires the predictive modeling of complex data, for example images and shapes. The main challenge when predicti…
Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker
James H Cole, Rudra PK Poudel, Dimosthenis Tsagkrasoulis +4
Machine learning analysis of neuroimaging data can accurately predict chronological age in healthy people and deviations from healthy brain ageing have been associated with cogniti…
Heritability maps of human face morphology through large-scale automated three-dimensional phenotyping
Dimosthenis Tsagkrasoulis, Pirro Hysi, Tim Spector +1
The human face is a complex trait under strong genetic control, as evidenced by the striking visual similarity between twins. Nevertheless, heritability estimates of facial traits…
Random Forests on Distance Matrices for Imaging Genetics Studies
Aaron Sim, Dimosthenis Tsagkrasoulis, Giovanni Montana
We propose a non-parametric regression methodology, Random Forests on Distance Matrices (RFDM), for detecting genetic variants associated to quantitative phenotypes representing th…