5 citations · 11 across the 5 of their papers we have counts for
6 papers
3D Grid-Attention Networks for Interpretable Age and Alzheimer's Disease Prediction from Structural MRI
Pradeep Lam, Alyssa H. Zhu, Iyad Ba Gari +2
We propose an interpretable 3D Grid-Attention deep neural network that can accurately predict a person's age and whether they have Alzheimer's disease (AD) from a structural brain…
Heritability estimates on resting state fMRI data using the ENIGMA analysis pipeline
Bhim M. Adhikari, Neda Jahanshad, Dinesh Shukla +8
Big data initiatives such as the Enhancing NeuroImaging Genetics through Meta-Analysis consortium (ENIGMA), combine data collected by independent studies worldwide to achieve more…
Evaluating 35 Methods to Generate Structural Connectomes Using Pairwise Classification
Dmitry Petrov, Alexander Ivanov, Joshua Faskowitz +5
There is no consensus on how to construct structural brain networks from diffusion MRI. How variations in pre-processing steps affect network reliability and its ability to disting…
Classification of Major Depressive Disorder via Multi-Site Weighted LASSO Model
Dajiang Zhu, Brandalyn C. Riedel, Neda Jahanshad +13
Large-scale collaborative analysis of brain imaging data, in psychiatry and neu-rology, offers a new source of statistical power to discover features that boost ac-curacy in diseas…
A Restaurant Process Mixture Model for Connectivity Based Parcellation of the Cortex
Daniel Moyer, Boris A Gutman, Neda Jahanshad +1
One of the primary objectives of human brain mapping is the division of the cortical surface into functionally distinct regions, i.e. parcellation. While it is generally agreed tha…
Structural Connectome Validation Using Pairwise Classification
Dmitry Petrov, Boris Gutman, Alexander Ivanov +4
In this work, we study the extent to which structural connectomes and topological derivative measures are unique to individual changes within human brains. To do so, we classify st…