Latest AI and machine learning research in geriatrics for healthcare professionals.
Gait assessment is a key clinical indicator of fall risk and overall health in older adults. However, standard clinical practice is largely limited to stopwatch-measured gait speed. We present a pipeline that leverages a 3D Human Mesh Recovery (HMR) model to extract gait parameters from recordings of older adults completing the Timed Up and Go (TUG) test. From videos recorded across different comm...
Background Individual clinical cognitive assessments (CCA) for Alzheimer's disease (AD) provide broad disease stratification but are limited in sensitivity and specificity, requiring integration of multiple CCA for optimal disease staging. Recent work from our lab suggests that neuro-metabolic and vascular dysregulation (MVD) occurs early in AD, prior to clinical symptoms, and may provide higher s...
ABSTRACT Background: RNA editing is a post-transcriptional modification that alters the sequence of an RNA transcript. Two types of RNA editing were f...
The biological definition of Alzheimer's disease (AD) relies on multi-modal neuroimaging, yet the clinical utility of positron emission tomography (PE...
Reliable recognition of standard cine cardiac MRI views is essential because each view determines which cardiac anatomy is visualized and which quanti...
Referring multi-object tracking (RMOT) is a task of associating all the objects in a video that semantically match with given textual queries or refer...
We present Camyla, a system for fully autonomous research within the scientific domain of medical image segmentation. Camyla transforms raw datasets i...
Reconstructing visual stimuli from non-invasive electroencephalography (EEG) remains challenging due to its low spatial resolution and high noise, par...
The advent of agentic multimodal models has empowered systems to actively interact with external environments. However, current agents suffer from a p...
Video depth estimation is essential for providing 3D scene structure in applications ranging from autonomous driving to mixed reality. Current end-to-...
Frailty and functional decline strongly influence treatment tolerance and outcomes in older patients with cancer, yet assessment is typically limited ...
Psychological stress is clinically relevant in cardio-oncology, yet it is typically assessed only through patient-reported outcome measures (PROMs) an...
Developing optical systems for free-space applications requires simulation tools that accurately capture turbulence-induced wavefront distortions and ...
Decreasing sequence length is a common way to accelerate transformers, but prior token reduction work often targets classification and reports proxy m...
Autonomous highway driving, especially for long-haul heavy trucks, requires detecting objects at long ranges beyond 500 meters to satisfy braking dist...
Alzheimer's disease (AD) is a neurodegenerative disorder that affects more than seven million people in the United States alone. AD currently has no c...
Computer vision models for chest X-ray interpretation hold significant promise for global healthcare, but their clinical value depends on equitable de...
Deep learning models utilizing longitudinal healthcare data have significantly advanced epidemiological research. However, contemporary transformer-ba...
End-to-end autonomous driving models based on Vision-Language-Action (VLA) architectures have shown promising results by learning driving policies thr...
We study high-dimensional mediation analysis in which exposures, mediators, and outcomes are all multivariate, and both exposures and mediators may be...