36 citations · 167 across the 20 of their papers we have counts for
4 papers · 1 filter
TimeMIL: Advancing Multivariate Time Series Classification via a Time-aware Multiple Instance Learning
Xiwen Chen, Peijie Qiu, Wenhui Zhu +5
Deep neural networks, including transformers and convolutional neural networks, have significantly improved multivariate time series classification (MTSC). However, these methods o…
Improving Normative Modeling for Multi-modal Neuroimaging Data using mixture-of-product-of-experts variational autoencoders
Sayantan Kumar, Philip Payne, Aristeidis Sotiras
Normative models in neuroimaging learn the brain patterns of healthy population distribution and estimate how disease subjects like Alzheimer's Disease (AD) deviate from the norm.…
Disentangling Alzheimer's disease neurodegeneration from typical brain aging using machine learning
Gyujoon Hwang, Ahmed Abdulkadir, Guray Erus +18
Neuroimaging biomarkers that distinguish between typical brain aging and Alzheimer's disease (AD) are valuable for determining how much each contributes to cognitive decline. Machi…
MAGIC: Multi-scale Heterogeneity Analysis and Clustering for Brain Diseases
Junhao Wen, Erdem Varol, Ganesh Chand +2
There is a growing amount of clinical, anatomical and functional evidence for the heterogeneous presentation of neuropsychiatric and neurodegenerative diseases such as schizophreni…