Exercise & Fitness

Early Detection of Cardiovascular Disease Risk Using Multi-Parameter Biomarker Analysis and Machine Learning: A Prospective Cohort Study

Cardiovascular disease (CVD) remains the leading cause of mortality globally, with many events occurring in individuals without prior diagnosed conditions. Early risk stratification using accessible biomarkers could enable timely intervention and reduce adverse outcomes. To evaluate the performance of a machine learning-based risk prediction model utilizing routine physiological parameters for ear...

Hepatic and abdominal adiposity in type 2 diabetes as assessed with machine learning on CT scans

The distribution of abdominal adipose depots and their mechanistic links to type 2 diabetes remain incompletely understood. This study elucidated the relationship between type 2 diabetes presence and quantitative abdominal imaging traits, including hepatic steatosis, liver and spleen size, and adipose distribution, using unenhanced computed tomography (CT) scans from a large-scale, racially divers...

Learning diverse and generic representations of the brain with large-scale multi-task pretraining

Large pretrained models developed and shared by actors with privileged access to data and compute have played a central role in the democratisation of...

Comparing the Treatment and Side Effects of Existing Bariatric Surgery Procedures: An Observational Study

Bariatric surgery is an established treatment for obesity and its associated comorbidities, including diabetes, hypertension, sleep apnea, and hyperch...

Infectious diseases, imposing density-dependent mortality on MHC/HLA variation, can account for balancing selection and MHC/HLA polymorphism

The human MHC transplantation loci (HLA-A, -B, -C, -DPB1, -DQB1, -DRB1) are the most polymorphic in the human genome. It is generally accepted this ...

GAIN-BRCA: a graph-based AI-net framework for breast cancer subtype classification using multiomics data.

MOTIVATION: Contextual integration of multiomic datasets from the same patient could improve the accuracy of subtype prediction algorithms to help wit...

Navigating the design of simulated exercising peers: insights from a participatory design study.

BACKGROUND: To fight sedentary lifestyles, researchers have introduced various technological interventions aimed at promoting physical activity throug...

Enhancing table tennis performance and physical fitness through digital technology: a quasi-experimental study based on the TPACK framework.

Educational digitization has made integrating digital technology into physical education a pivotal strategy for transforming pedagogy. Guided by the T...

Revolutionizing health monitoring: Integrating transformer models with multi-head attention for precise human activity recognition using wearable devices.

BACKGROUND: A daily activity routine is vital for overall health and well-being, supporting physical and mental fitness. Consistent physical activity ...

Dissecting the Predictors of Cyber-Aggression Through an Explainable Machine Learning Model.

The general aggression model (GAM) suggests that cyber-aggression stems from individual characteristics and situational contexts. Previous studies hav...

Estimation of Central Aortic Pressure Waveforms by Combination of a Meta-Learning Neural Network and a Physics-Driven Method.

The accurate non-invasive detection and estimation of central aortic pressure waveforms (CAPW) are crucial for reliable treatments of cardiovascular s...

Towards nation-wide analytical healthcare infrastructures: A privacy-preserving augmented knee rehabilitation case study

The purpose of this paper is to contribute towards the near-future privacy-preserving big data analytical healthcare platforms, capable of processin...

TPepRet: a deep learning model for characterizing T-cell receptors-antigen binding patterns.

MOTIVATION: T-cell receptors (TCRs) elicit and mediate the adaptive immune response by recognizing antigenic peptides, a process pivotal for cancer im...

Ultra-Low Complexity On-Orbit Compression for Remote Sensing Imagery via Block Modulated Imaging

The growing field of remote sensing faces a challenge: the ever-increasing size and volume of imagery data are exceeding the storage and transmissio...

How to Manage My Data? With Machine--Interpretable GDPR Rights!

The EU GDPR is a landmark regulation that introduced several rights for individuals to obtain information and control how their personal data is bei...

Wearable Accelerometer Foundation Models for Health via Knowledge Distillation

Modern wearable devices can conveniently record various biosignals in the many different environments of daily living, enabling a rich view of indiv...

Explainable machine learning for neoplasms diagnosis via electrocardiograms: an externally validated study

Background: Neoplasms remains a leading cause of mortality worldwide, with timely diagnosis being crucial for improving patient outcomes. Current di...

Risk factor identification and classification of malnutrition among under-five children in Bangladesh: Machine learning and statistical approach

This study aims to understand the factors that resulted in under-five children's malnutrition from the Multiple Indicator Cluster (MICS-2019) nation...

Prompt Transfer for Dual-Aspect Cross Domain Cognitive Diagnosis

Cognitive Diagnosis (CD) aims to evaluate students' cognitive states based on their interaction data, enabling downstream applications such as exerc...

"Give me the code" -- Log Analysis of First-Year CS Students' Interactions With GPT

The impact of Large Language Models (LLMs) like GPT-3, GPT-4, and Bard in computer science (CS) education is expected to be profound. Students now h...