Geriatrics

Cell as Point: One-Stage Framework for Efficient Cell Tracking

Conventional multi-stage cell tracking approaches rely heavily on detection or segmentation in each frame as a prerequisite, requiring substantial resources for high-quality segmentation masks and increasing the overall prediction time. To address these limitations, we propose CAP, a novel end-to-end one-stage framework that reimagines cell tracking by treating Cell as Point. Unlike traditional ...

mmWave Radar for Sit-to-Stand Analysis: A Comparative Study with Wearables and Kinect

This study explores a novel approach for analyzing Sit-to-Stand (STS) movements using millimeter-wave (mmWave) radar technology. The goal is to develop a non-contact sensing, privacy-preserving, and all-day operational method for healthcare applications, including fall risk assessment. We used a 60GHz mmWave radar system to collect radar point cloud data, capturing STS motions from 45 participan...

ML-Based Framework to Predict the Severity of the Symptomatology in Patients with Post-Acute COVID-19 Syndrome.

The paper describes a cohort of patients with post-acute COVID-19 syndrome, evaluated for the first time between week 3 and week 12 from the onset of ...

Using Deep Learning to Suggest Treatment for Proximal Humerus Fractures.

Proximal humeral fractures are among the most common fractures seen in emergency departments. Accurately diagnosing and selecting the most appropriate...

Genome-wide association neural networks identify genes linked to family history of Alzheimer's disease.

Augmenting traditional genome-wide association studies (GWAS) with advanced machine learning algorithms can allow the detection of novel signals in av...

Explainable deep neural networks for predicting sample phenotypes from single-cell transcriptomics.

Recent advances in single-cell RNA-Sequencing (scRNA-Seq) technologies have revolutionized our ability to gather molecular insights into different phe...

Efficient Brain Imaging Analysis for Alzheimer's and Dementia Detection Using Convolution-Derivative Operations

Alzheimer's disease (AD) is characterized by progressive neurodegeneration and results in detrimental structural changes in human brains. Detecting ...

Anatomy-Guided Radiology Report Generation with Pathology-Aware Regional Prompts

Radiology reporting generative AI holds significant potential to alleviate clinical workloads and streamline medical care. However, achieving high c...

Hateful Meme Detection through Context-Sensitive Prompting and Fine-Grained Labeling

The prevalence of multi-modal content on social media complicates automated moderation strategies. This calls for an enhancement in multi-modal clas...

MimIR: An Extensible and Type-Safe Intermediate Representation for the DSL Age

Traditional compilers, designed for optimizing low-level code, fall short when dealing with modern, computation-heavy applications like image proces...

TATAA: Programmable Mixed-Precision Transformer Acceleration with a Transformable Arithmetic Architecture

Modern transformer-based deep neural networks present unique technical challenges for effective acceleration in real-world applications. Apart from ...

Deep learning assisted quantitative analysis of Aβ and microglia in patients with idiopathic normal pressure hydrocephalus in relation to cognitive outcome.

Neuropathologic changes of Alzheimer disease (AD) including Aβ accumulation and neuroinflammation are frequently observed in the cerebral cortex of pa...

Disentangling Interpretable Factors with Supervised Independent Subspace Principal Component Analysis

The success of machine learning models relies heavily on effectively representing high-dimensional data. However, ensuring data representations capt...

Generative forecasting of brain activity enhances Alzheimer's classification and interpretation

Understanding the relationship between cognition and intrinsic brain activity through purely data-driven approaches remains a significant challenge ...

Matrix-by-matrix multiplication algorithm with $O(N^2log_2N)$ computational complexity for variable precision arithmetic

We show that assuming the availability of the processor with variable precision arithmetic, we can compute matrix-by-matrix multiplications in $O(N^...

Taming the Long Tail in Human Mobility Prediction

With the popularity of location-based services, human mobility prediction plays a key role in enhancing personalized navigation, optimizing recommen...

Learning autonomous driving from aerial imagery

In this work, we consider the problem of learning end to end perception to control for ground vehicles solely from aerial imagery. Photogrammetric s...

Exploiting Longitudinal Speech Sessions via Voice Assistant Systems for Early Detection of Cognitive Decline

Mild Cognitive Impairment (MCI) is an early stage of Alzheimer's disease (AD), a form of neurodegenerative disorder. Early identification of MCI is ...

Copula-Linked Parallel ICA: A Method for Coupling Structural and Functional MRI brain Networks

Different brain imaging modalities offer unique insights into brain function and structure. Combining them enhances our understanding of neural mech...

SGUQ: Staged Graph Convolution Neural Network for Alzheimer's Disease Diagnosis using Multi-Omics Data

Alzheimer's disease (AD) is a chronic neurodegenerative disorder and the leading cause of dementia, significantly impacting cost, mortality, and bur...