Exercise & Fitness

Spinal cord injury impact on skin temperature regulation during graded exercise: metaheuristic data mining-based predictions.

People with spinal cord injury (SCI) show impaired thermoregulation during exercise, making skin temperature a noninvasive indicator. This study applies hybrid Extreme Learning Machine (ELM) models optimized with Ant Lion, Dragonfly, and Evolution Strategy algorithms to predict skin and core temperature dynamics during graded arm-crank exercise in 32 participants (16 SCI, 16 controls). The Dragonf...

Patients' Attitudes and Beliefs Toward Artificial Intelligence Use in Cancer Care: Cross-Sectional Survey Study.

BACKGROUND: Artificial intelligence (AI) is being rapidly integrated into oncologic care, yet little is known about how patients perceive these applications. Understanding patient perceptions is critical to ensuring AI applications align with their needs and preferences. OBJECTIVE: This study aimed to evaluate oncology patients' attitudes and beliefs on the use of AI across clinical touchpoints in...

Treating those not ready to quit smoking: Doing harm while trying to help?

INTRODUCTION: Motivation-phase smoking treatment can increase treatment reach and abstinence in persons unmotivated to quit smoking. However, Motivati...

Integrated Prediction System for Individualized Ovarian Stimulation and Ovarian Hyperstimulation Syndrome Prevention: Algorithm Development and Validation.

BACKGROUND: Accurately predicting ovarian response and determining the optimal starting dose of follicle-stimulating hormone (FSH) remain critical yet...

ECG and PPG Signals-Based Premature Ventricular Contraction Detection Methods: A Review, Key Challenges, and Future Directions.

Premature ventricular contraction (PVC) is a common cardiac arrhythmia, and its timely and automated detection is crucial for preventing life-threaten...

[Efficacy prediction of acupuncture and moxibustion combined with conventional treatment for PCOS-IR based on real-world data: machine learning and interpretability analysis].

OBJECTIVE: To construct an efficacy prediction model for polycystic ovary syndrome with insulin resistance (PCOS-IR) treated with acupuncture and moxi...

Linking ecological strategies to niche breadth: interpretable machine learning unravels community patterns of nirS-type aerobic denitrifiers along oxygen gradients in drinking water reservoirs.

Aerobic denitrifying bacteria are increasingly recognized for nitrogen removal in deep drinking-water reservoirs, yet how dissolved oxygen (DO) gradie...

Gamified Physical Education and Cognitive Performance Among Chinese Secondary School Students: Cross-Sectional Moderation Mediation Study.

BACKGROUND: Educators are exploring new methods to educate beyond the classroom as global concerns about students' cognitive, emotional, and social we...

Bridging machine learning and clinical practice: a multicentre nomogram for 90-day graft failure risk stratification in heart transplantation.

BACKGROUND: Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, base...

The genetic foundations of convergent traits.

Convergent phenotypic evolution, the independent acquisition of similar or nearly identical traits in multiple species, is widespread throughout the t...

Harnessing artificial intelligence for cardio-oncology:Towards a new future of cardiovascular care for the cancer patient.

Artificial intelligence (AI) offers new opportunities in cardio-oncology for early detection, risk stratification, and personalized management of card...

ChatGPT Outperforms Personal Trainers in Answering Common Exercise Training Questions.

Since its launch, the chatbot ChatGPT has gained significant popularity and may serve as a valuable resource for evidence-based exercise training advi...

Predicting Treatment Outcomes in Patients With Psoriatic Arthritis or Axial Spondyloarthritis: An Artificial Intelligence-Driven Approach.

OBJECTIVE: To develop machine learning (ML) models to predict the probability at baseline of achieving low disease activity (LDA) and high health-rela...

AI-Driven Smart Sportswear for Real-Time Fitness Monitoring Using Textile Strain Sensors.

Wearable biosensors have revolutionized human performance monitoring by enabling real-time assessment of physiological and biomechanical parameters. H...

A 192-Channel 1D CNN-Based Neural Feature Extractor in 65nm CMOS for Brain-Machine Interfaces.

We present a 192-channel 1D convolutional neural network (1D CNN) based neural feature extractor for Brain-Machine Interfaces (BMI) that achieves stat...

Establishment and validation of a machine learning model to stratify malnutrition risk in hospitalized older patients with chronic heart failure.

BACKGROUND AND OBJECTIVES: Malnutrition among older hospitalized adults with chronic heart failure (CHF) is associated with adverse clinical outcomes,...

Analysis of Clinical Improvement at 90 Days After Varicose Vein Surgery Using Machine Learning.

Outcomes after intervention for chronic venous insufficiency (CVI) is difficult to predict. This study aimed to develop machine learning (ML) models t...

Prediction of mortality, bleeding, and ischaemic events in patients with cancer and acute coronary syndrome: a model development and validation study.

BACKGROUND: Accurate assessment of mortality, bleeding, and atherothrombotic risk in patients with cancer and acute coronary syndrome could inform nov...

From non-specific biomarker to targeted action: transdiagnostic and sex-specific drivers of high-CRP status in severe mental illness across the FondaMental Advanced Centers of Expertise (FACE) cohorts.

BACKGROUND AND OBJECTIVES: Low-grade systemic inflammation contributes to the pathophysiology of severe mental illness (SMI) in a substantial subset o...

Gut microbiome signatures associated with depression and obesity.

UNLABELLED: Depression and obesity are highly comorbid and likely involve common risk factors and pathophysiological mechanisms, which could crosslink...