Latest AI and machine learning research in exercise & fitness for healthcare professionals.
Serum high-density lipoprotein (HDL) and low-density lipoprotein (LDL) cholesterol levels are associated with risk factors for various diseases and are related to anthropometric measures. However, controversy remains regarding the best anthropometric indicators of the HDL and LDL cholesterol levels. The objectives of this study were to identify the best predictors of HDL and LDL cholesterol using ...
Electroencephalography (EEG)-based motor imagery (MI) brain-computer interface (BCI) technology has the potential to restore motor function by inducing activity-dependent brain plasticity. The purpose of this study was to investigate the efficacy of an EEG-based MI BCI system coupled with MIT-Manus shoulder-elbow robotic feedback (BCI-Manus) for subjects with chronic stroke with upper-limb hemipar...
PURPOSE: Robotics-assisted tilt-table (RTT) technology allows neurological rehabilitation therapy to be started early thus alleviating some secondary ...
Computer vision models that estimate body mass index (BMI) from facial features offer a non-invasive, low-cost alternative to physical measurement, wi...
Recently, there has been a growing adoption of protein language models (PLMs) in biomedical science. Their embeddings provide a rich numerical represe...
Existing action quality assessment (AQA) datasets and methods rely primarily on visual inputs such as RGB and pose, overlooking physiological dynamics...
Background Glucagon-like peptide-1 (GLP-1) receptor agonists and sodium-glucose cotransporter-2 (SGLT2) inhibitors are increasingly used for type 2 di...
Motivation: Machine learning has emerged as a powerful accelerator for identifying PET-hydrolyzing enzymes (PETases). Yet, published models are often ...
Background. Phthalates are hypothesised to act as metabolic disruptors, and machine learning applied to the National Health and Nutrition Examination ...
Existing general-purpose biomedical knowledge graphs tend to focus on disease mechanisms and drug repurposing, leaving multiomic and wellness-relevant...
Background: Low birth weight remains a primary driver of neonatal and infant mortality in Ethiopia. Machine learning models can assist early risk iden...
Falls among older adults represent a major public health challenge driven by complex, time-varying interactions across multiple risk domains. Effectiv...
Motivation: Disease mechanisms emerge from the coordinated activity of multiple biological pathways, rather than from individual pathways acting in is...
Abstract Background The gut microbiome has been widely studied in the context of obesity, and yet the reported associations vary widely across populat...
Foundation models (FMs) trained on large-scale accelerometer data have been proposed as general-purpose feature extractors for health monitoring, but ...
Autonomous rehabilitation systems must not only recognize human motion but also provide structured feedback to support users without continuous therap...
The aim of this paper is to (1) identify textual and visual themes and sub-themes associated with the #wellbeing hashtag on Instagram, (2) assess thei...
Recent advances in artificial intelligence have accelerated the discovery of bioactive peptides by enabling computational exploration of the vast pept...
Although deep neural network-based remote sensing object detectors have achieved strong performance, they remain vulnerable to adversarial perturbatio...
BACKGROUND: Liberation from invasive mechanical ventilation (IMV) is a central therapeutic objective in acute respiratory failure (ARF). While lung-pr...