Prevention

Using machine learning to identify the strongest personal, school, and family correlates of youth mental health and well-being.

Research has identified numerous personal, school, and family factors associated with youth mental health, yet it remains unclear which correlates best predict mental health outcomes accurately. This study used machine learning to identify the strongest personal, school, and family correlates of mental well-being, overall mental health problems, and internalizing (anxiety and depression) and exter...

Smartphone App Using Reinforcement Learning for Obesity: Single-Arm Feasibility Study.

BACKGROUND: While behavioral interventions remain an evidence-based treatment for obesity, they often require long durations and frequent sessions. To address this, we hypothesized that interventions delivered in daily life via a smartphone app combined with personalized optimization using reinforcement learning may effectively support behavior changes. OBJECTIVE: This study aimed to develop and e...

Ryanodine receptor 2 mutations in catecholaminergic polymorphic ventricular tachycardia: From molecular mechanisms to precision medicine.

Catecholaminergic polymorphic ventricular tachycardia is a classic example of the successful transfer of genetic cardiology from gene discovery to imp...

Comment on "Measuring diet intake in adolescents: Relative validation of an artificial intelligence enhanced, image assisted mobile application".

GlucoseGo: a simple tool to predict hypoglycaemia during exercise in type 1 diabetes.

AIMS/HYPOTHESIS: This study aimed to develop an accessible tool, derived using machine learning, to predict hypoglycaemia risk at the start of exercis...

Integrative metabolomics and machine learning reveal the toxic mechanisms of elaidic acid in polycystic ovary syndrome.

BACKGROUND: Polycystic ovary syndrome (PCOS) is characterized by reproductive dysfunction and metabolic disturbances, including obesity, insulin resis...

Non-pharmacological treatment of AECOPD.

Acute exacerbations of chronic obstructive pulmonary disease (AECOPDs) are acute events characterized by rapid worsening of dyspnea, cough, and sputum...

Familial colorectal cancer: risk factors, screening strategies and personalized medicine.

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide, with approximately 25-30 % of cases exhibiting a familial compo...

Living on the flood line: Constructing and validating a combined multidimensional resilience index for rural riverine floodplain communities.

Resilience analysis is crucial for developing interventions that mitigate riverine flood risk in the context of global environmental change and sustai...

A review of ageing related biomarkers in breath.

The growing ageing population presents significant challenges for healthcare systems, particularly in monitoring age-related physiological decline. Ag...

Electroencephalography-Based Machine Learning Models for Predicting Ketogenic Diet Outcomes in Pediatric Drug-Resistant Epilepsy.

BACKGROUND: Ketogenic diet therapy (KDT) is an established treatment for drug-resistant epilepsy (DRE); however, methods for predicting its effectiven...

Assessment of Predictive Factors That Shorten Duration of Treatment in Patients With Multiple Myeloma Using AI: Real-World Longitudinal Study Using Data From Medical Data Vision Claims Database.

BACKGROUND: With the availability of newer therapies, the duration of therapy (DoT) shortens with each increasing line of treatment in Japanese patien...

Predicting cardiopulmonary exercise testing outcomes in congenital heart disease through multimodal data integration and geometric learning.

Cardiopulmonary exercise testing (CPET) provides a comprehensive assessment of functional capacity by measuring key physiological variables including ...

Artificial intelligence in head and neck cancer rehabilitation services: current state and future perspectives.

PURPOSE OF REVIEW: This review evaluates the current state of artificial intelligence (AI) in head and neck cancer (HNC) rehabilitation services by ma...

[AI and clinical reasoning : between promises and the risks of "deskilling"].

The rise of AI in healthcare offers major potential for diagnosis and learning but also exposes to a worrying risk of "deskilling." Recent data from c...

APOE genotype and the effect of statins on lipid outcomes: A meta-analysis.

AIM: APOE genotype may affect statin therapy response. We conducted a meta-analysis to update and quantify this association across various outcomes. M...

Long-term landscape change drives shifts in functional traits of wintering waterbirds along China's Yellow Sea Coast.

Coastal wetlands are biodiversity hotspots facing severe threats from anthropogenic activities. Understanding how functional trait distribution of wat...

Leveraging machine learning to identify gendered stereotypes and body image concerns on diet and fitness online forums.

The pervasive expectations about ideal body types in Western society can lead to body image concerns, dissatisfaction, and in extreme cases, eating di...

Automated prescription of therapeutic exercise for shoulder impingement syndrome using literature-driven rule generation architecture.

BACKGROUND: Shoulder impingement syndrome (SIS) is a common musculoskeletal disorder that requires individualized therapeutic exercise prescription. H...

Linking Individual Motives to the Type of Exercise and Sport Activity: Toward Recommendations for Optimal Activity Matching Through a Machine Learning Approach.

BACKGROUND: To effectively promote exercise and sport behavior, it is often emphasized that individual motives should be more strongly considered. The...