Exercise & Fitness

Accelerating the discovery of industrial PET-degrading enzymes: Evolving paradigms from bioprospecting to computational discovery.

Polyethylene terephthalate (PET) waste remains a major environmental and resource challenge, and enzymatic depolymerization offers a promising route for recovering terephthalic acid and ethylene glycol under aqueous conditions for closed-loop PET recycling. However, the practical deployment of PET-degrading enzymes is constrained by substrate crystallinity and morphology, limited thermal robustnes...

Machine learning prediction of customer satisfaction in fitness centres.

Customer satisfaction in fitness centres is critical for fostering loyalty, higher spending, cross-buying, and positive recommendations. This study seeks to develop a predictive model of gym users' satisfaction, identify its main determinants, and optimise predictive accuracy through machine learning techniques. Data from 10,368 users across five Spanish fitness centre chains were analysed. Five m...

A machine learning-based framework for predicting hypertension using serum hematological factors.

Hypertension (HTN) is a leading global cause of cardiovascular disease (CVD) and all-cause mortality, underscoring the need for early detection and in...

Microbial Named Entity Recognition and Normalisation for AI-assisted Literature Review and Meta-Analysis.

MOTIVATION: Manual curation of biomedical literature is slow and error-prone and while large language models trained on general texts have shown to be...

Fitness translocation: improving variant effect prediction with biologically-grounded data augmentation.

MOTIVATION: Data scarcity limits the characterization of protein fitness landscapes and the development of accurate variant effect prediction models. ...

Fully automated artificial intelligence-based echocardiographic analysis for global longitudinal strain monitoring and cancer therapy-related cardiac dysfunction detection in breast cancer patients.

AIMS: Global longitudinal strain (GLS) is essential for the early detection of cancer therapy-related cardiac dysfunction (CTRCD). A fully automated e...

Hepatic Steatosis Severity Prediction in Nonobese Individuals: Machine Learning Model Development and Validation.

BACKGROUND: Steatotic liver disease affects 40% of nonobese individuals, but existing screening tools inadequately detect and stage disease severity i...

Comparison Between Robotic and Conventional Walking Recovery Training Methods in People With Spinal Cord Injury: Systematic Review With Pairwise and Network Meta-Analysis.

OBJECTIVE: To compare robotic body weight supported treadmill training (RBWSTT), overground robotic exoskeleton training (ORET), and conventional phys...

Incorporating dietary information to enhance polygenic prediction models with applications to body mass index and type 2 diabetes.

BACKGROUND: Polygenic predictors can enhance screening for metabolism-related traits such as body mass index (BMI) and type 2 diabetes (T2D). However,...

Machine learning to improve the prediction of Large for Gestational Age (LGA) neonates: a cohort study.

BACKGROUND: Prediction of Large for Gestational Age (LGA) risk is important as it can enable earlier, more effective interventions, and avoid or mitig...

AVSeg-XAI: Deep learning framework for A/V segmentation with vascular features reveals retinal oculomics as biomarker for cardiovascular disease.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of mortality across the globe. Conventional risk stratification often depends on invasiv...

Multimodal engagement estimation in paediatric robot-assisted gait training: integrating physiological sensing and biomechanical interaction.

BACKGROUND: Patients' engagement plays a crucial role in the effectiveness of robot-assisted gait training (RAGT), particularly in paediatric neuroreh...

The role of metabolic health in neurostructural and cognitive alterations in bipolar disorders.

BACKGROUND: Bipolar disorders (BD) rank among the most disabling conditions, affecting millions worldwide. Cognitive impairment in BD is linked with b...

Accuracy of thoracolumbar pedicle screw placement using intraoperative CT navigation versus 3D-printed patient-specific guides integrated with virtual surgical planning: a comparative study.

BACKGROUND: 3D-printed patient-specific pedicle screw guides (3DPSG) may provide accuracy comparable to intraoperative CT navigation (CTNav). Our 3DPS...

Prognostic prediction models for psoriatic arthritis in psoriasis: A systematic review.

BACKGROUND: Psoriatic arthritis is a chronic inflammatory arthropathy that affects up to 22% of individuals with psoriasis. Identifying patients at hi...

Identification of depression types and key influencing factors among rural elderly in China: a comprehensive analysis based on machine learning and network analysis.

BACKGROUND: Depression poses a severe public health challenge for older adults, especially in rural China. In rural settings, the heavy burden of chro...

Heart Rate Monitors for the Estimation of Physical Activity in Patients With Cardiovascular Disease: Systematic Review.

BACKGROUND: Heart rate (HR) monitoring by wearable devices offers a physiological, personalized, and continuous method for assessing physical activity...

The Warmth of Medicine: The Irreplaceability of Doctors in the Era of Artificial Intelligence.

This article argues that despite the remarkable advances of artificial intelligence (AI) in medicine -including demonstrated capabilities in image rec...

Visceral adipose tissue inflammation in endometrial cancer.

BACKGROUND: Obesity is the largest risk factor for endometrial cancer. Body Mass Index (BMI) does not fully capture obesity's metabolic and inflammato...

Determinants of childhood and adolescent obesity: An explainable AI approach using the ICAD database.

OBJECTIVES: To identify the biological, behavioural, and socio-demographic determinants of childhood and adolescent obesity and evaluate how their rel...