Exercise & Fitness

Myocardial relaxation, left ventricular filling, and exercise capacity in older subjects with dyspnea.

With aging, left ventricular (LV) early diastolic lengthening declines. Delayed or dyssynchronous untwisting and relaxation may slow and reduce filling and contribute to elevated diastolic pressures. Segmental variations in the timing of early diastolic relaxation may impair LV suction during exercise and impact LV stroke volume reserve, especially in heart failure with preserved ejection fraction...

Forecasting Dropout in Home-Based Movement Rehabilitation after Stroke with Sensors and Machine Learning.

Adherence to home-based rehabilitation can support recovery after stroke, yet many patients disengage within the first few weeks. While prior studies have examined perseverance in small samples or under supervised settings, little is known about early behavioral signals of long-term perseverance in large, unsupervised cohorts. This study analyzes one of the largest datasets on home rehabilitation ...

Early Identification of Mobility Limitations in Community-Dwelling Middle-Aged and Older Adults: Development of a Prediction Model Based on a Prospective Cohort.

BACKGROUND: With the aging of the global population, preventing the onset of mobility limitations is considered a worldwide public health priority. OB...

Multidimensional balance assessment and machine learning gait stability prediction in elderly women.

To develop and validate a comprehensive balance assessment scale specifically designed for elderly women and construct predictive models for gait stab...

Dynamic machine learning model integrating resting energy expenditure for predicting postoperative complications after gastrectomy for gastric cancer.

PURPOSE: To investigate whether perioperative resting energy expenditure (REE) dynamics improve prediction of postoperative complications after gastre...

Breaking the culture habit: Complementing culture-based veterinary diagnostics with metagenomic data -A case study of feline and canine skin infections.

BACKGROUND: Skin infections have been described as the primary cause for veterinary small animal practice visits, frequently requiring topical and sys...

SPISE index and ensemble machine learning refine cardiovascular risk stratification in stage 0-3 CKM syndrome.

BACKGROUND: While the single-point insulin sensitivity estimator (SPISE) shows promise as an insulin resistance biomarker, its association with cardio...

Ventral hernia repair in emergency settings. A machine learning model to predict post-operative complications.

BACKGROUND: Emergency ventral hernia repair remains a challenging procedure due to patient instability, contaminated surgical fields, and heterogeneit...

Inspiratory muscle training devices for chronic lung disease management: current evidence and future directions.

INTRODUCTION: Inspiratory muscle training (IMT) is a potential adjunct therapy to improve inspiratory muscle strength and endurance, exercise capacity...

Evaluation of image quality between hybrid iterative reconstruction and deep learning reconstruction in low dose abdominopelvic CT in low body mass index individuals.

The study aimed to compare image quality between hybrid iterative reconstruction and deep learning image reconstruction (DLIR) in low dose contrast en...

Drug Response Profile-Based Machine Learning Enables Strategic Cell Line and Compound Selection for Drug Development.

MOTIVATION: Early-stage drug discovery relies on testing compounds across a limited set of cell lines, making it challenging to capture biological div...

Development and validation of a clinlabomics-based machine-learning model for noninvasive risk stratification of moderate-to-severe OSA.

PURPOSE: Obstructive sleep apnea (OSA) is a highly prevalent sleep disorder strongly associated with adverse cardiometabolic and neurocognitive outcom...

Machine learning reveals proteome-encoded growth determinants underlying metabolic versatility of Rhodopseudomonas palustris on lignin-derived aromatics.

Lignin depolymerization generates mixtures of aromatic compounds that are promising carbon sources for microbial bioconversion, yet the constraints go...

Effective real-time self-rehabilitation exercise monitoring and correctness system for low back pain management.

In the modern era of working, Musculoskeletal Disorders (MSDs) are increasing drastically. One of the leading causes of MSD is Low Back Pain (LBP). Pa...

Integrative transcriptomic and machine learning approach reveals key DDR genes and predictors of ami risk in the Bangladeshi population.

Acute Myocardial Infarction (AMI) is a significant contributor to cardiovascular death, with rising prevalence in Bangladesh. Although DNA damage cont...

Comparison of automated robotic arm-assisted PET/computed tomography-guided metabolic bone marrow biopsy with conventional bone marrow trephine biopsy for evaluating bone marrow infiltration in newly diagnosed lymphoma.

OBJECTIVES: Bone marrow involvement (BMI) upstages lymphoma and influences prognosis and treatment. Conventional bone marrow trephine biopsy (BMTB) ma...

Prevalence and determinants of sacroiliac joint bone marrow oedema in the general population in Germany: a population-based cross-sectional study.

BACKGROUND: MRI-detected bone marrow oedema in sacroiliac joints is central to diagnosing axial spondyloarthritis, influencing treatment decisions inc...

An upper limb stroke rehabilitation exercise video dataset.

Stroke is one of the leading causes of disability worldwide with a disproportionately high burden in low and middle-income countries. In such countrie...

Machine Learning-Driven Simulations of the SARS-CoV-2 Fitness Landscape from Deep Mutational Scanning Experiments.

Predicting protein variant effects is a key challenge in preparing for pathogenic viral strains, understanding mutation-linked diseases, and designing...

From Fitness to Cognition: Machine-Learning Prediction of Cognitive Performance Using Physiological Parameters in Healthy Adults.

INTRODUCTION: Current cognitive tasks are not suitable for frequent monitoring of cognitive function in healthy adults. Increasing evidence suggests t...