Yanghee Im

This study evaluates how sample size affects machine learning performance in classifying dementia stages using subcortical brain features from 2,511 ADNI samples.

The paper introduces a 3D brain geometry toolkit for multisite neuroimaging analysis, showing subcortical shape measures improve diagnostic and treatment prediction compared to traditional volume features.

The paper introduces a scalable toolkit for 3D surface-based brain analysis, demonstrating its utility in mapping subcortical shape variations across 21 international samples.

This paper applies a spherical harmonics-based deep learning model to MRI-derived brain shape metrics to predict age, sex, and Alzheimer's disease diagnosis, showing strong performance in classification and regression tasks.