4 citations · 7 across the 6 of their papers we have counts for
6 papers
Comparative Study of Anatomical and Learned Features in AI Models for Structural Brain MRI
Boyang Yu, Miquel Lopez Escoriza, Long Chen +3
In this work, we comprehensively evaluate three popular feature-extraction paradigms in AI-based neuroimaging modeling: (1) computation of anatomical surfaces and volumes, (2) supe…
Learning Sparse Latent Predictive Foundation Model for Multimodal Neuroimaging
Haoxu Huang, Long Chen, Jingyun Chen +8
Brain MRIs are routinely acquired as multiple complementary sequences with unique contrast weighting, including T1-weighed imaging (T1w) anatomic and fluid-sensitive T2-weighted (T…
Cerebra: A Multidisciplinary AI Board for Multimodal Dementia Characterization and Risk Assessment
Sheng Liu, Long Chen, Zeyun Zhao +16
Modern clinical practice increasingly depends on reasoning over heterogeneous, evolving, and incomplete patient data. Although recent advances in multimodal foundation models have…
Quantum Sensing MRI for Noninvasive Detection of Neuronal Electrical Activity in Human Brains
Yongxian Qian, Ying-Chia Lin, Seyedehsara Hejazi +12
Neuronal electrical activity underlies human cognition including perception, attention, memory, language, and decision-making. Yet its direct, noninvasive measurement in the living…
3D Foundation Model for Generalizable Disease Detection in Head Computed Tomography
Weicheng Zhu, Haoxu Huang, Huanze Tang +10
Head computed tomography (CT) imaging is a widely-used imaging modality with multitudes of medical indications, particularly in assessing pathology of the brain, skull, and cerebro…
-penalized Multinomial Regression: Estimation, inference, and prediction, with an application to risk factor identification for different dementia subtypes
Ye Tian, Henry Rusinek, Arjun V. Masurkar +1
High-dimensional multinomial regression models are very useful in practice but have received less research attention than logistic regression models, especially from the perspectiv…