Fang Ji

Improving DASH adherence after midlife promotes better late-life cognition and brain health: the SG70 Study

This study shows that better adherence to the DASH diet in midlife and early elderhood improves late-life verbal memory and brain health through structural and neurovascular mechanisms.

Mind the Gap: Does Brain Age Improve Alzheimer's Disease Prediction?

This study compares brain age models and direct models for predicting Alzheimer's Disease outcomes, finding that direct models perform better despite brain age models having larger training data.

Longer scans boost prediction and cut costs in brain-wide association studies

The paper shows longer scans improve prediction accuracy in brain-wide association studies while reducing costs, with 30-minute scans being the most cost-effective.

WMH-DualTasker: A weakly-supervised deep learning model for automated white matter hyperintensities segmentation and visual rating prediction

WMH-DualTasker is a weakly-supervised deep learning model that segments white matter hyperintensities and predicts visual ratings, outperforming supervised methods on benchmark datasets.

Optimizing Biophysical Large-Scale Brain Circuit Models With Deep Neural Networks

This paper introduces DELSSOME, a deep learning framework that accelerates biophysical brain circuit model optimization, enabling faster parameter estimation and lifespan trajectory analysis of cortical E/I ratios.

Additive effects of cerebrovascular disease functional connectome phenotype and plasma p-tau181 on longitudinal neurodegeneration and cognitive outcomes

The paper examines how cerebrovascular disease markers and plasma p-tau181 interact to affect brain connectivity, grey matter volume, and cognitive decline over time.

DeepResBat: deep residual batch harmonization accounting for covariate distribution differences

DeepResBat improves MRI data harmonization by addressing covariate distribution differences, outperforming existing methods while avoiding false associations.

Stage dependent differential influence of metabolic and structural networks on memory across Alzheimer's disease continuum

The paper examines how structural and metabolic network integrity influences memory across Alzheimer's disease stages, finding pathology-dependent changes in these relationships.