Exercise & Fitness

Interpretable machine learning model for predicting operative difficulty in robotic total mesorectal excision for mid-low rectal cancer.

Precise preoperative prediction of surgical complexity in robot-assisted total mesorectal excision (R-TME) is essential for optimizing surgical strategies. The current study aimed to construct an interpretable machine learning (ML) model to anticipate operative difficulty in sphincter-preserving R-TME. Retrospective data from 449 patients diagnosed with mid-to-low rectal cancer undergoing R-TME at...

Depression-Related Nutritional Risk and Physical Performance in Middle- to Older-Aged Adults: Cross-Sectional Secondary Analysis of Tree-Based and Regression Approaches.

BACKGROUND: Depressive symptoms are linked to nutritional vulnerability and functional decline in aging populations, but their relationships with nutritional risk and lower-extremity physical performance are often examined separately. Tree-based exploratory approaches may provide transparent subgroup characterization. OBJECTIVE: This study aimed to examine the cross-sectional associations of depre...

Artificial intelligence in cardio-kidney-metabolic care: Transforming integrated disease management through data-informed innovation.

Artificial intelligence (AI) is rapidly transforming the landscape of chronic medical conditions, such as cardio-kidney-metabolic (CKM) issues linked ...

Using Machine Learning to Analyze the Predictors of Life Satisfaction: Focus on Lifestyle Attitudes and Psychological Factors.

OBJECTIVES: Life satisfaction is an essential indicator of quality of life, and enhancing it can contribute to individual well-being strategies. Becau...

Prediction of Cardiovascular Risk Using Machine Learning Based on Maximal Oxygen Consumption, Physical Fitness, and Anthropometry.

Cardiovascular risk factors in adolescence, often persist into adulthood, with low cardiorespiratory fitness representing one of the strongest predict...

The role of artificial intelligence in structuring youth athletic training: implications for personality and motivational development.

BACKGROUND: This study examines the impact of AI-based training approaches on young athletes' motivation and personality traits. The analysis focuses ...

MALICoT: A pilot cross-sectional study analyzing the effects of power training and age on endomysium content and fiber area in the soleus muscle of adult males.

The cross-sectional Master Athletic Laboratory Study of Intramuscular Connective Tissue (MALICoT, DRKS00015764) examined effects of athletic exercise ...

Deep learning-based CT-derived vertebral bone mineral density and metformin therapy: a longitudinal study in the Multi-Ethnic Study of Atherosclerosis.

OBJECTIVE: Evidence on metformin's skeletal effects remains conflicting. We emulated a target trial to evaluate associations between metformin therapy...

Assessing Image Quality and Diagnostic Performance of Quadruple-Low Coronary CT Angiography with Deep Learning in High-BMI Patients.

RATIONALE AND OBJECTIVES: To examine the feasibility of a quadruple-low protocol in coronary computed tomography angiography (CCTA) assisted by the de...

Explainable ensemble machine learning for predicting diabetes mellitus and identifying key risk factors: a population-based study in northern Bangladesh.

Diabetes mellitus (DM) is an escalating global public health concern, with a rapidly increasing burden in low- and middle-income countries, including ...

Multi-task deep learning for sub-clinical screening of mood and sleep disturbances using physical activity biomarkers.

BACKGROUND: Sub-clinical screening for mood disorders and sleep disturbances remains challenging due to limited accessibility of mental health screeni...

Innovative strategies for early detection of cardiotoxicity: artificial intelligence and multi-modality collaborative models.

Cancer therapeutics account for a significant proportion of new drug development, reflecting advances in diagnosis, treatment, and disease control. Ho...

The impact of GenAI-assisted instructional design on the teaching ability of pre-service physical education teachers.

In view of a pain point in the field of textual logic generation and physiological load quantification in physical education (PE) instructional design...

A hybrid AI vision model for single-camera tracking of rehabilitation exercises: a proof of concept in clinical settings.

Accurate measurement of range of motion (ROM) during physical rehabilitation is traditionally achieved using goniometers or multi-camera, marker-based...

Exercise-related genes predicts overall survival and tumor immune microenvironment, and identifies the biological role of SLC52A2 in breast cancer.

BACKGROUND: Breast cancer (BRCA) is the most common malignant tumor in women, with prognoses differing markedly by molecular subtype. Exercise is know...

Associations of body mass index and metabolic health with stroke risk in a large prospective cohort with time updated covariates.

The global prevalence of overweight and obesity is rising, and recent studies have established an independent contribution of adiposity to stroke risk...

Identifying necessary conditions for medical students' adoption of AI in the future practice: a survey study in Canada.

BACKGROUND: As artificial intelligence (AI) technologies become increasingly embedded in healthcare, the readiness of future physicians to adopt these...

Early-life proteomic and microbiome features signal obesity risk across 26 years of follow-up.

UNLABELLED: Childhood obesity is rising globally. Yet, few studies have examined the microbiome and proteome in early childhood in relation to this ou...

Impact of Unfractionated Heparin Use on Maternal Bone Mineral Density During Pregnancy: A Retrospective Study Using AI-Assisted Radiographic Analysis.

PURPOSE: This study aimed to evaluate the impact of unfractionated heparin (UFH) use during pregnancy on maternal bone mineral density (BMD) by assess...

AI-assisted case-based learning and flipped classroom to improve clinical decision-making: a randomized controlled trial in reproductive medicine.

BACKGROUND: Efficient training of reproductive medicine clinicians is critical in the context of declining global fertility and increasing infertility...