Ferris Ramadan

Project Personnel, University of Arizona

2 active projects

Training_v4

I would like to use this workspace purely for educational purposes only. It will be used to demonstrate to students various data analysis approaches using large datasets and to familiarize them with All of Us cloud storage workflow.

Scientific Questions Being Studied

I would like to use this workspace purely for educational purposes only. It will be used to demonstrate to students various data analysis approaches using large datasets and to familiarize them with All of Us cloud storage workflow.

Project Purpose(s)

  • Educational

Scientific Approaches

To produce aggregate summary statistics and regression models for various measurement variables available in All of Us data.

Anticipated Findings

This exploratory analysis will enable us to explore heterogeneity in anthropometric measures among various racial-ethnic groups

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

Collaborators:

  • Heidi Steiner - Graduate Trainee, University of Arizona
  • Claire Devaney - Undergraduate Student, University of Arizona

NAFLD

Our primary research objective is to evaluate whether standard diagnostic tools for NAFLD, such as ALT and TG, are the strong predictors for disease between various races and ethnicities. We will further evaluate whether a recent prediction model developed using…

Scientific Questions Being Studied

Our primary research objective is to evaluate whether standard diagnostic tools for NAFLD, such as ALT and TG, are the strong predictors for disease between various races and ethnicities. We will further evaluate whether a recent prediction model developed using the IMI Direct cohorts developed using individuals classified as white European ancestry applies to other racial and ethnic groups. See initial paper here: 10.1371/journal.pmed.1003149

Project Purpose(s)

  • Disease Focused Research (fatty liver disease)

Scientific Approaches

We will have two strategies for selecting the clinical variables. For models 1–3, we will select variables based on clinical accessibility and their established association with fatty liver from existing literature without applying statistical procedures for data reduction. For model 4, a pairwise Pearson correlation matrix will be used for feature selection of the clinical variables by placing a pairwise correlation threshold of r > 0.8, and we will then selected the collinear variables. Feature selection will be undertaken in the combined cohort (diabetes and non-diabetes) in order to maximize sample size and statistical power.

Anticipated Findings

We anticipate to identify differences in the utility of diagnostic measures predicting NAFLD.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Geography
  • Income Level

Research Team

Owner:

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