The World Health Organization recommends one ultrasound before 24 weeks of pregnancy. Recent developments with technology-assisted ultrasound increase ultrasound access to patients in low- and middle-income countries. This study is the evaluation of the implementation of technology-assisted ultrasounds in 7 antenatal clinics in Zambia. The goal is to understanding the acceptability and feasibility of the ultrasounds, and ultimately to publish information helpful to policymakers and clinic directors involved in implementing similar programs in low-resource settings.

The goal of this study is to better understand how executive function skills (like planning, organization, and problem solving) can impact blood sugar levels in people with type 1 diabetes. We also want to understand how insulin pump and continuous glucose monitor use impact blood sugar levels based on executive function skills.

We are surveying engineering doctoral students in the US to learn more about what factors lead them to continue or leave their training. We are especially interested in their perceptions of the climate of their programs.

The purpose of this study is to understand the behaviors and attitudes related to online grocery shopping among parents with children age 1-5 years old. The aim is to develop online food retail nudges to discourage fruit drink purchases and promote healthier substitutes. The ultimate goal is to decrease consumption of sugar-sweetened beverages in childhood as these are associated with increased risk of diet-related chronic diseases, such as obesity and type 2 diabetes.

We aim to develop, field-test, and promote improved ways to measure and assess the public health hazards associated with sanitation systems and practices in sub-Saharan Africa, with the overall goal of informing sanitation planning and implementation at community levels. This will involve learning more about the range and distribution of sanitation technologies encountered in two cities of Africa (i.e., Kampala and Lusaka). Learning more about the levels of microbiological hazard in onsite sanitation systems especially septic tanks and other technology-specific lessons can be usefully incorporated in citywide sanitation improvement tools.

The purpose of this research study is to follow new parents with cystic fibrosis for 5 years to learn more about how their health changes when they become parents. The information we gather in this study will be used to inform future interventions to help people with CF successfully prepare for and transition into parenthood

Our team developed a calculator to help oncologists better estimate prognosis in patients with metastatic breast cancer (MBC). Using this information, our team developed a prognostic calculator to predict risk of death within 30 days for patients with MBC. For this information to impact care, it will have to be used in clinical practice. In order to increase the likelihood of successful adoption of the calculator into clinical practice, we will study its implementation and evaluate its impact. In this study, we will seek the input of doctors, nurses, and advance practice providers who care for patients with MBC to better understand the factors that encourage and dissuade discussion of prognosis and use of such a prognostic tool.

To develop an artificial intelligence (AI) and machine learning (ML) process focused on physicians' variability during the pre-treatment peer review processes and assess the impact of the process in the RT work system on patient safety.

Predictive modeling has recently attracted a lot of attention from organizations trying to leverage AI and big data to improve their work processes such as decision-making. However, real-world problems are rarely well-formulated machine learning problems. Practitioners have to supply a well-defined predictive target to operationalize a predictive model. In such cases, they often resort to using observed variables to approximate the actual construct of interest. For example, people have used high sales numbers as a proxy for a good employee. Proxy label selection is a recurring challenge when predictive ML is applied to real-world problems. The purpose of this interview study is to understand how ML practitioners select proxy labels, evaluate proxy labels, and iterate through the different tasks involved.

The purpose of this study is to create a registry that will collect clinical data from participants attending UNC Hospitals who may present with metastatic cancer and are evaluated to receive radiation therapy. We hope to create a registry that future studies can pull from to study the impacts of radiation therapy on patient cancer outcomes.