Latest AI and machine learning research in prevention for healthcare professionals.
Cancer is increasingly recognized as a metabolic disease with strong nutritional determinants. Recent advances in multi-omics technologies and artificial intelligence (AI), especially machine learning (ML), have enabled novel integrative frameworks to decode complex interactions among diet, metabolism, and tumor biology. To systematically synthesize evidence on how multi-omics and AI/ML approaches...
The ongoing war in Ukraine has exposed young adults to sustained psychological stress, elevating their risk of developing post-traumatic stress disorder (PTSD). In a case–control study of 698 individuals, we investigated associations between PTSD, dietary patterns, disordered eating behaviours, and hematological parameters. PTSD was associated with greater adherence to restrictive diets—including ...
Transthoracic echocardiography (TTE) is a widely available tool for diagnosing and managing heart failure but has limited predictive value for surviva...
Preterm birth, defined as birth occurring before 37 weeks of gestation, poses a significant and enduring public health challenge, with substantial emo...
The potential of artificial intelligence (AI) to personalize dietary and exercise advice for obesity management is increasingly evident. However, the ...
Sleep, physical activity, and nutrition (SPAN) are major modifiable risk factors for cardiovascular disease, yet the minimum and optimal combined impr...
Generalized anxiety disorder (GAD) is a common psychiatric condition, with unknown etiology and pathophysiology. Recent studies have suggested alterat...
The global prevalence of overweight and obesity continues escalating, driven by environmental factors and lifestyle behaviors leading to cardiovascula...
Regular physical activity preserves functional independence in older adults, yet care-home residents often miss out because personalized supervision i...
Disrupted brain iron metabolism and activated ferroptosis during ageing constitute significant precursors to neurodegenerative diseases. However, whet...
Monitoring the effectiveness of statin therapy in patients with dyslipidemia is essential for ensuring optimal treatment outcomes. The current standar...
Cardiorespiratory fitness (CRF) is a powerful predictor of cardiovascular events and overall mortality, often surpassing traditional risk factors in p...
Limited information linking dietary intake to gut metagenomic data in bariatric surgery patients is available. We examined whether there were correlat...
Children with attention-deficit/hyperactivity disorder (ADHD) often face barriers to participating in organized sports, particularly when physical edu...
Cardiovascular diseases (CVD) are complex disorders involving the impaired function of blood vessels or the heart. Several risk factors contribute to ...
Standard LDL-C equations were derived in cohorts largely untreated with modern combination diabetes therapies. With medication-treated patients compri...
Clinical improvement and survival benefit after transcatheter aortic valve replacement (TAVR) are difficult to predict. Despite the identification of ...
Colorectal cancer is the third leading cause of cancer-related deaths in the United States, and colonoscopy remains the gold standard for early detect...
Personalized data-driven interventions for depression are much needed. Here, we leveraged N-of-1 machine learning (ML) to optimally target behavioral ...
Polygenic predictors can enhance screening for biomedical conditions, such as metabolism-related traits and diseases, but explain limited phenotypic v...