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Metabolomic data can potentially enable accurate, non-invasive and low-cost prediction of coronary artery disease. Regression-based analytical approaches however might fail to fully account for interactions between metabolites, rely on a…
It is known that the primary source of dietary vitamin C is fruit and vegetables and the plasma level of vitamin C has been considered a good surrogate biomarker of vitamin C intake by fruit and vegetable consumption. To combine the…
Cardiovascular disease (CVD) continues to be the major cause of death globally, calling for predictive models that not only handle diverse and high-dimensional biomedical signals but also maintain interpretability and privacy. We create a…
Measurement error arises commonly in clinical research settings that rely on data from electronic health records or large observational cohorts. In particular, self-reported outcomes are typical in cohort studies for chronic diseases such…
We study the correlation of the occurrence of coronary heart disease (CHD) with the presence of the single-nucleotide polymorphism (SNP) at the -308 position of the tumor necrosis factor alpha (TNF-$\alpha$) gene. We also consider the…
Coronary artery disease remains one of the leading causes of mortality globally. Despite advances in revascularization treatments like PCI and CABG, postoperative stroke is inevitable. This study aims to develop and evaluate a sophisticated…
In this paper, we discuss the impact of the Covid-19 pandemic on alcohol consumption habit changes among healthcare workers in the United States. We utilize multiple supervised and unsupervised machine learning methods and models such as…
Diabetes is one of the deadliest diseases in the world and affects nearly 10 percent of the global adult population. Fortunately, powerful new technologies allow for a consistent and reliable treatment plan for people with diabetes. One…
The integration of Internet-of-Things and pervasive computing in medical devices have made the modern healthcare system "smart". Today, the function of the healthcare system is not limited to treat the patients only. With the help of…
Among the most impactful diabetic complications are diabetic retinopathy, the leading cause of blindness among working class adults, and cardiovascular disease, the leading cause of death worldwide. This study describes the development of…
Background and Objective: Only about 14 % of eligible EU citizens finally participate in colorectal cancer (CRC) screening programs despite it being the third most common type of cancer worldwide. The development of CRC risk models can…
Type 1 Diabetes (T1D) is an autoimmune disease leading to insulin insufficiency. Thus, patients require lifelong insulin therapy, which has a side effect of hypoglycemia. Hypoglycemia is a critical state of decreased blood glucose levels…
Metabolic Syndrome (MetS) is a cluster of interrelated risk factors that significantly increases the risk of cardiovascular diseases and type 2 diabetes. Despite its global prevalence, accurate prediction of MetS remains challenging due to…
Excessive alcohol consumption causes disability and death. Digital interventions are promising means to promote behavioral change and thus prevent alcohol-related harm, especially in critical moments such as driving. This requires real-time…
Although previous observational studies have shown associations between serum 25-hydroxyvitamin D (25(OH)D) concentration and metabolic syndrome, this association has not yet been investigated among Aboriginal and Torres Strait Islander…
Coronary microvascular dysfunction (CMD), characterized by impaired regulation of blood flow in the coronary microcirculation, plays a key role in the pathogenesis of ischemic heart disease and is increasingly recognized as a contributor to…
Purpose: The application of Cox Proportional Hazards (CoxPH) models to survival data and the derivation of Hazard Ratio (HR) is well established. While nonlinear, tree-based Machine Learning (ML) models have been developed and applied to…
Leveraging health administrative data (HAD) datasets for predicting the risk of chronic diseases including diabetes has gained a lot of attention in the machine learning community recently. In this paper, we use the largest health records…
COVID-19 pandemic has introduced a new lifestyle due to lockdown. The impact was on food habits, working hours, and sleeping patterns. The goal of this study is to detect lifestyle changes caused by confinement during the COVID-19 pandemic,…
Chronic kidney disease (CKD) is a significant public health challenge, often progressing to end-stage renal disease (ESRD) if not detected and managed early. Early intervention, warranted by silent disease progression, can significantly…