Sarah Beaver
Graduate Trainee, University of North Texas
5 active projects
Diabetes
Scientific Questions Being Studied
The effects of different blood components on glucose levels in hyperglycemic patients. We want to create a predictive model which can estimate change in level of glucose by changing blood component concentration, such as RBC counts, electrolyte concentration, etc. , in Type 2 diabetes patients.
Project Purpose(s)
- Disease Focused Research (type 1 diabetes mellitus)
- Ancestry
Scientific Approaches
We will analyze the lab results of 150,000 plus individuals in the All Of Us Research workbench. We will try to find a pattern between glucose levels compared to blood components levels in normal and diabetic patients in Python and determine which blood component is associated with change in blood glucose levels. Once we determine these components, we want to create a predictive model which will determine which blood component can assist in blood glucose maintenance.
Anticipated Findings
The results of our study, once published, will assist doctors in making better decisions to regulate glucose levels with drugs, dietary, and lifestyle changes as well as if any medication changes levels of any blood components, our model can predict how it will affect glucose levels in the patients.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierResearch Team
Owner:
- Yashu Vashishath - Graduate Trainee, University of North Texas
- Sarah Beaver - Graduate Trainee, University of North Texas
Recent: Type 2 Diabetes Subtyping (Tier 6)
Scientific Questions Being Studied
The effects of different blood components on glucose levels in hyperglycemic patients. We want to create a predictive model which can estimate change in level of glucose by changing blood component concentration, such as RBC counts, electrolyte concentration, etc. , in Type 2 diabetes patients.
Project Purpose(s)
- Disease Focused Research (hyperglycemia)
- Ancestry
Scientific Approaches
We will analyze the lab results of 150,000 plus individuals in the All Of Us Research workbench. We will try to find a pattern between glucose levels compared to blood components levels in normal and diabetic patients in Python and determine which blood component is associated with change in blood glucose levels. Once we determine these components, we want to create a predictive model which will determine which blood component can assist in blood glucose maintenance.
Anticipated Findings
The results of our study, once published, will assist doctors in making better decisions to regulate glucose levels with drugs, dietary, and lifestyle changes as well as if any medication changes levels of any blood components, our model can predict how it will affect glucose levels in the patients.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierResearch Team
Owner:
- Yashu Vashishath - Graduate Trainee, University of North Texas
- Sarah Beaver - Graduate Trainee, University of North Texas
Tier 5 - Type 2 Diabetes Subtyping
Scientific Questions Being Studied
The effects of different blood components on glucose levels in hyperglycemic patients. We want to create a predictive model which can estimate change in level of glucose by changing blood component concentration, such as RBC counts, electrolyte concentration, etc. , in Type 2 diabetes patients.
Project Purpose(s)
- Disease Focused Research (hyperglycemia)
Scientific Approaches
We will analyze the lab results of 150,000 plus individuals in the All Of Us Research workbench. We will try to find a pattern between glucose levels compared to blood components levels in normal and diabetic patients in Python and determine which blood component is associated with change in blood glucose levels. Once we determine these components, we want to create a predictive model which will determine which blood component can assist in blood glucose maintenance.
Anticipated Findings
The results of our study, once published, will assist doctors in making better decisions to regulate glucose levels with drugs, dietary, and lifestyle changes as well as if any medication changes levels of any blood components, our model can predict how it will affect glucose levels in the patients.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierResearch Team
Owner:
- Yashu Vashishath - Graduate Trainee, University of North Texas
- Serdar Bozdag - Mid-career Tenured Researcher, University of North Texas
- Sarah Beaver - Graduate Trainee, University of North Texas
- Islam Ebeid - Research Fellow, University of North Texas
- Mohammad Al Olaimat - Graduate Trainee, University of North Texas
All_of_Us data information
Scientific Questions Being Studied
Need to look at different data types and their association with diseases for a given patient. There are multiple data modalities but it is not provided what kind of features does each data modality has and is the feature associated with any disease suffered by the patient.
Project Purpose(s)
- Population Health
Scientific Approaches
Different data analysis techniques as well as similarity association among the patients. We will use genomic sequence, EHR, survey, fitbit and physical measurements data.
Anticipated Findings
We want to determine what features would help in calculating similarity among different patients with same diseases.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierDisease Prediction
Scientific Questions Being Studied
Comparing Bayesian Deep Learning techniques on disease prediction to regular deep learning models.
Project Purpose(s)
- Educational
Scientific Approaches
Surveys and labs. Bayesian Deep learning, Neural Networks
Anticipated Findings
If bayesian deep learning models provide better prediction when including probability percentage of predicted outcome.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierResearch Team
Owner:
- Yashu Vashishath - Graduate Trainee, University of North Texas
- Sarah Beaver - Graduate Trainee, University of North Texas
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