Related papers: A Micro-Macro Machine Learning Framework for Predi…
Obesity is a complex disease and its prevalence depends on multiple factors related to the local socioeconomic, cultural and urban context of individuals. Many obesity prevention strategies and policies, however, are horizontal measures…
Built environment features (BEFs) refer to aspects of the human constructed environment, which may in turn support or restrict health related behaviors and thus impact health. In this paper we are interested in understanding whether the…
Diabetes is a serious worldwide health issue, and successful intervention depends on early detection. However, overlapping risk factors and data asymmetry make prediction difficult. To use extensive health survey data to create a machine…
As we gain access to a greater depth and range of health-related information about individuals, three questions arise: (1) Can we build better models to predict individual-level risk of ill health? (2) How much data do we need to…
Electronic health records (EHRs) have become a platform for data-driven surveillance on a granular level in recent years. In this paper, we make use of EHRs for early prevention of childhood obesity. The proposed method simultaneously…
Childhood anemia remains a major public health challenge in Nepal and is associated with impaired growth, cognition, and increased morbidity. Using World Health Organization hemoglobin thresholds, we defined anemia status for children aged…
Childhood malnutrition remains a major public health concern in Nepal and other low-resource settings, while conventional case-finding approaches are labor-intensive and frequently unavailable in remote areas. This study provides the first…
Clinical risk prediction models often underperform in real-world settings due to poor calibration, limited transportability, and subgroup disparities. These challenges are amplified in high-dimensional multimodal cancer datasets…
Obesity is one of the leading health concerns in the United States. Researchers and health care providers are interested in understanding factors affecting obesity and detecting the likelihood of obesity as early as possible. In this paper,…
Understanding the key factors shaping environmental hazard exposures and their associated environmental injustice issues is vital for formulating equitable policy measures. Traditional perspectives on environmental injustice have primarily…
Malnutrition among pregnant women is a major public health challenge in Ethiopia, increasing the risk of adverse maternal and neonatal outcomes. Traditional statistical approaches often fail to capture the complex and multidimensional…
This study presents a web-based interactive health risk prediction tool designed to assess diabetes risk using machine learning models. Built on the 2015 CDC BRFSS dataset, the study evaluates models including Logistic Regression, Random…
In this study, we delve into the intricate relationships between diabetes and a range of health indicators, with a particular focus on the newly added variable of income. Utilizing data from the 2015 Behavioral Risk Factor Surveillance…
Obesity is a critical global health issue driven by dietary, physiological, and environmental factors, and is strongly associated with chronic diseases such as diabetes, cardiovascular disorders, and cancer. Machine learning has emerged as…
Student's mental health problems have been explored previously in higher education literature in various contexts including empirical work involving quantitative and qualitative methods. Nevertheless, comparatively few research could be…
Advances in IoT technologies combined with new algorithms have enabled the collection and processing of high-rate multi-source data streams that quantify human behavior in a fine-grained level and can lead to deeper insights on individual…
The growing instability of both global and domestic economic environments has increased the risk of financial distress at the household level. However, traditional econometric models often rely on delayed and aggregated data, limiting their…
Student mental health is an increasing concern in academic institutions, where stress can severely impact well-being and academic performance. Traditional assessment methods rely on subjective surveys and periodic evaluations, offering…
Globally, the number of obese patients has doubled due to sedentary lifestyles and improper dieting. The tremendous increase altered human genetics, and health. According to the world health organization, Life expectancy dropped from 80 to…
National Health and Nutritional Status Survey (NHANSS) is conducted annually by the Ministry of Health in Negara Brunei Darussalam to assess the population health and nutritional patterns and characteristics. The main aim of this study was…