BACKGROUND: Current evidence regarding the effects of serum Klotho among patients with metabolic syndrome (MetS) is scarce. This study explored the relationship between serum Klotho levels and the odds of chronic kidney disease (CKD) in middle-aged a...
BACKGROUND: Psoriatic arthritis (PSA) is an inflammatory joint disease associated with psoriasis (PSO) that can be easily missed. Existing PSA screening tools ignore objective serologic indicators. The aim of this study was to develop a disease scree...
BACKGROUND: The intake of dietary antioxidants and glycolipid metabolism are closely related to chronic kidney disease (CKD), particularly among individuals with abdominal obesity. Nevertheless, the cumulative effect of multiple comorbid risk factors...
Several pieces of evidence have been reported regarding the association between periodontitis and systemic diseases. Despite the emphasized significance of prevention and early diagnosis of periodontitis, there is still a lack of a clinical tool for ...
AIMS: Natriuretic peptide-based pre-heart failure screening has been proposed in recent guidelines. However, an effective strategy to identify screening targets from the general population, more than half of which are at risk for heart failure or pre...
International journal of environmental research and public health
Dec 19, 2024
BACKGROUND: Gastrointestinal (GI) distress is prevalent and often persistent among cancer survivors, impacting their quality of life, nutrition, daily function, and mortality. GI health screening is crucial for preventing and managing this distress. ...
PURPOSE: This study aims to harness machine learning techniques, particularly the Random Survival Forest (RSF) model, to assess the impact of depression on cardiovascular disease (CVD) mortality among hypertensive patients. A key objective is to eluc...
OBJECTIVE: To develop and validate a machine learning model incorporating dietary antioxidants to predict cardiovascular disease (CVD)-cancer comorbidity and to elucidate the role of antioxidants in disease prediction.
AIM: To analyse the risk factors contributing to the prevalence of periodontitis among clusters of patients with diabetes and to examine the clustering patterns of clinical blood biochemical indicators.
PURPOSE: Epidemiologic studies are important in assessing risk factors of mortality. Machine learning (ML) is efficient in analyzing multidimensional data to unravel dependencies between risk factors and health outcomes.