Prevention

Prediction model of subacromial pain syndrome in assembly workers using shoulder range of motion and muscle strength based on support vector machine.

Subacromial pain syndrome (SAPS) is the most common upper-extremity musculoskeletal problem among workers. In this study, a machine learning model was built to predict and classify the presence or absence of SAPS in assembly workers with shoulder joint range of motion (ROM) and muscle strength data using support vector machine (SVM). Permutation importance was used to determine important variables...

Deep learning-based dynamic ventilatory threshold estimation from electrocardiograms.

BACKGROUND AND OBJECTIVE: The ventilatory threshold (VT) marks the transition from aerobic to anaerobic metabolism and is used to assess cardiorespiratory endurance. A conventional way to assess VT is cardiopulmonary exercise testing, which requires a gas analyzer. Another method for measuring VT involves calculating the heart rate variability (HRV) from an electrocardiogram (ECG) by computing the...

A perspective on the use of deep deterministic policy gradient reinforcement learning for retention time modeling in reversed-phase liquid chromatography.

Artificial intelligence and machine learning techniques are increasingly used for different tasks related to method development in liquid chromatograp...

The potential of Spirulina platensis to substitute antibiotics in Japanese quail diets: impacts on growth, carcass traits, antioxidant status, blood biochemical parameters, and cecal microorganisms.

The development of antibiotic-resistant microorganisms prompted the investigation of possible antibiotic substitutes. As a result, the purpose of the ...

An accurate aging clock developed from large-scale gut microbiome and human gene expression data.

Accurate measurement of the biological markers of the aging process could provide an "aging clock" measuring predicted longevity and enable the quanti...

Mechanisms of Exercise Intolerance Across the Breast Cancer Continuum: A Pooled Analysis of Individual Patient Data.

PURPOSE: The purpose of this study is to evaluate the prevalence of abnormal cardiopulmonary responses to exercise and pathophysiological mechanism(s)...

Artificial intelligence in sport: Exploring the potential of using ChatGPT in resistance training prescription.

OpenAI's Chat Generative Pre-trained Transformer (ChatGPT) technology enables conversational interactions with applications across various fields, inc...

Can ChatGPT provide appropriate meal plans for NCD patients?

OBJECTIVES: Dietary habits significantly affect health conditions and are closely related to the onset and progression of non-communicable diseases (N...

From Microcosm to Macrocosm: The -Omics, Multiomics, and Sportomics Approaches in Exercise and Sports.

This article explores the progressive integration of -omics methods, including genomics, metabolomics, and proteomics, into sports research, highlight...

Development of artificial intelligence-based slow-motion echocardiography and clinical usefulness for evaluating regional wall motion abnormalities.

The diagnostic accuracy of exercise stress echocardiography (ESE) for myocardial ischemia requires improvement, given that it currently depends on the...

Effect of 4-weeks exercise program using wearable hip-assist robot (EX1) in older adults: one group pre- and post- test.

BACKGROUND: Older adults have muscle loss and are at risk of falling. Recently, research in the healthcare field has been actively conducted, and Sams...

Correlation Between Statin Use and Symptomatic Venous Thromboembolism Incidence in Patients With Ankle Fracture: A Machine Learning Approach.

BACKGROUND: Identifying factors that correlate with the incidence of venous thromboembolism (VTE) has the potential to improve VTE prevention and posi...

Learning Skill Training Schedules From Domain Experts for a Multi-Patient Multi-Robot Rehabilitation Gym.

A robotic gym with multiple rehabilitation robots allows multiple patients to exercise simultaneously under the supervision of a single therapist. The...

Exploring novel ANGICon-EIPs through ameliorated peptidomics techniques: Can deep learning strategies as a core breakthrough in peptide structure and function prediction?

Dairy-derived angiotensin-I-converting enzyme inhibitory peptides (ANGICon-EIPs) have been regarded as a relatively safe supplementary diet-therapy st...

ChatGPT: a tool for scientific writing or a threat to integrity?

The use of ChatGPT as a tool for writing and knowledge integration raises concerns about the potential for its use to replace critical thinking and ac...

Leaf Extract-Induced Apoptosis in the MCF-7 Breast Cancer Cell Line by Increasing Intracellular Oxidative Stress.

BACKGROUND: is one of the plants used in the diet of Iranian people. Previous studies have investigated the antioxidant and antibacterial effects of ...

Classification of patients with chronic disease by activation level using machine learning methods.

Patient Activation Measure (PAM) measures the activation level of patients with chronic conditions and correlates well with patient adherence behavior...

Natural language processing of online support group postings reveals patients' perspectives on strategies for managing psoriasis.

Psoriasis is a chronic skin disorder, and patients encounter high physical and psychosocial burdens. Social media forums feature extensive patient-gen...

Mitigating underreported error in food frequency questionnaire data using a supervised machine learning method and error adjustment algorithm.

BACKGROUND: Food frequency questionnaires (FFQs) are one of the most useful tools for studying and understanding diet-disease relationships. However, ...

A Robot-Assisted Framework for Rehabilitation Practices: Implementation and Experimental Results.

One of the most interesting characteristics of collaborative robots is their ability to be used in close cooperation scenarios. In industry, this faci...