2 citations · 5 across the 5 of their papers we have counts for
6 papers
TAMI: Temporally Aligned, Missingness-Aware, and Interpretable Multimodal Fusion for Mental Health Assessment in Older Adults with Mild Cognitive Impairment
Merna Bibars, Bolaji Omofojoye, Allan I. Levey +3
Depression and anxiety in older adults with Mild Cognitive Impairment (MCI) are frequently underdiagnosed due to limited access to care. Multimodal analysis of remote clinical inte…
Non-linear associations of amyloid- with resting-state functional networks and their cognitive relevance in a large community-based cohort of cognitively normal older adults
Junjie Wu, Benjamin B Risk, Taylor A James +6
Background: Non-linear alterations in brain network connectivity may represent early neural signatures of Alzheimer's disease (AD) pathology in cognitively normal older adults. Und…
Agentic AI for Scaling Diagnosis and Care in Neurodegenerative Disease
Andrew G. Breithaupt, Michael Weiner, Alice Tang +14
United States healthcare systems are struggling to meet the growing demand for neurological care, particularly in Alzheimer's disease and related dementias (ADRD). Generative AI bu…
Feasibility of Detecting Cognitive Impairment and Psychological Well-being among Older Adults Using Facial, Acoustic, Linguistic, and Cardiovascular Patterns Derived from Remote Conversations
Xiaofan Mu, Merna Bibars, Salman Seyedi +9
The aging society urgently requires scalable methods to monitor cognitive decline and identify social and psychological factors indicative of dementia risk in older adults. Our mac…
Feasibility of assessing cognitive impairment via distributed camera network and privacy-preserving edge computing
Chaitra Hegde, Yashar Kiarashi, Allan I Levey +3
INTRODUCTION: Mild cognitive impairment (MCI) is characterized by a decline in cognitive functions beyond typical age and education-related expectations. Since, MCI has been linked…
Privacy-Preserving Eye-tracking Using Deep Learning
Salman Seyedi, Zifan Jiang, Allan Levey +1
The expanding usage of complex machine learning methods like deep learning has led to an explosion in human activity recognition, particularly applied to health. In particular, as…