Latest AI and machine learning research in geriatrics for healthcare professionals.
Introduction. Distinct temperature patterns have long been recognized to correlate with fevers of differing etiologies. While the use of wearable sensors for high-frequency temperature monitoring (HFTM) on a near minute-by-minute basis has been shown to detect fevers earlier than standard-of-care nursing vital sign assessments in hospitalized patients, leveraging these high-resolution datasets to ...
The development of autonomous vehicles (AVs) usually relies heavily on data-driven artificial intelligence (AI) models that require large volumes of sensor data with ground-truth annotations. While modular architectures are widely used, end-to-end driving paradigms offer a promising alternative by directly mapping sensor inputs to control actions. However, their adoption is limited by challenges i...
Embodied AI increasingly relies on queryable semantic maps built from pre-trained vision-language models to enable zero-shot Object Goal Navigation (O...
Activities of daily living (ADLs) provide important indicators of functional decline in people living with dementia, motivating the need for continuou...
Acoustic biomarkers show promise for detecting Alzheimer's Disease (AD), yet whether the cues driving diagnostic AI align with those salient to human ...
Pretrained EEG foundation models are increasingly proposed for clinical decoding, but their transfer across populations and robustness to negative con...
End-to-end autonomous driving systems commonly follow a cascaded two-stage pipeline where a perception stage compresses multi-modal sensor inputs into...
Abstract Background: Deep Brain Stimulation (DBS) surgery is a treatment of choice for movement disorders, and utilizes an implanted electrical pulse ...
Background: Cognitive behavioural therapy (CBT) is the most frequently used and recommended therapy program for mental health conditions, including fo...
INTRODUCTION: Cognitive syndrome diagnosis (Normal, Mild Cognitive Impairment (MCI), Dementia) is important for summarizing disease status and predict...
Acquiring reading proficiency, unlike spoken language, requires the brain to engage several specialized neural systems to map visual symbols (letters)...
Optical Character Recognition (OCR) for Persian remains substantially less mature than for Latin-script languages despite Persian being spoken by more...
INTRODUCTION: The biomarker-based amyloid/ tau/ neurodegeneration (A/T/N) framework has become a popular staging method for Alzheimer's disease (AD) r...
Introduction: Cerebral amyloid angiopathy (CAA) is characterized by amyloid-beta deposition in cortical and leptomeningeal vessels and associated with...
Scaling laws describe how model performance improves as the amount of training data increases, and recent theories such as the zeta law suggest that s...
People with Down syndrome have higher age-specific mortality rates compared to the general population as well as peers with other intellectual and dev...
Deep learning classifiers applied to structural MRI (sMRI) have achieved high performance in detecting Alzheimer's Disease (AD), yet systematic invest...
Background. Predicting conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is central to trial enrichment and care planning, y...
Latent diffusion models (LDMs) enable efficient high-resolution image synthesis by denoising in a VAE-compressed latent space. However, fixed visual t...
Real-time EEG classification on edge devices is bottlenecked by the floating-point arithmetic of conventional neural networks. We investigated Differe...