Lauryn Bruce
Graduate Trainee, University of California, San Diego
6 active projects
Personal and Family History of Cancer
Scientific Questions Being Studied
I am creating this workspace to store notebooks created from published work: Keeler Bruce L, Paul P, Kim KK, Kim J, Keegan TH, Hiatt RA, Ohno-Machado L, All of Us Research Program Investigators. Family and personal history of cancer in the All of Us research program for precision medicine. PLoS One. 2023 Jul 17;18(7):e0288496.
Project Purpose(s)
- Disease Focused Research (cancer)
Scientific Approaches
This study was published with All of Us version 4 data release. Personal and Family history of cancer was explored.
Anticipated Findings
Findings have been published: Keeler Bruce L, Paul P, Kim KK, Kim J, Keegan TH, Hiatt RA, Ohno-Machado L, All of Us Research Program Investigators. Family and personal history of cancer in the All of Us research program for precision medicine. PLoS One. 2023 Jul 17;18(7):e0288496.
Demographic Categories of Interest
- Race / Ethnicity
- Age
- Education Level
- Income Level
Data Set Used
Registered TierResearch Team
Owner:
- Lauryn Bruce - Graduate Trainee, University of California, San Diego
Collaborators:
- Seohyun Park - Graduate Trainee, University of California, San Diego
- Jun Qian - Other, All of Us Program Operational Use
early fetal loss detection
Scientific Questions Being Studied
Can we use wearable data to detect and predict early fetal loss? There are potential negative physical and psychological consequences for women who experience EFL. If it becomes possible to detect this event before it occurs, we can mitigate some of those consequences or even potentially intervene to prevent the event.
Project Purpose(s)
- Population Health
Scientific Approaches
I plan on using datasets featuring information coming from wearables. I will use time series analyses to analyze the data coming from these wearables.
Anticipated Findings
I expect that we might be able to predict which women are expected to experience EFL. This would be the first study to build prediction models to test that using wearable data.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierResearch Team
Owner:
- Tamar Schaap - Graduate Trainee, University of California, San Diego
- Lauryn Bruce - Graduate Trainee, University of California, San Diego
Debiasing Health Algorithms
Scientific Questions Being Studied
Health algorithms often biased against underrepresented populations. Here, we hope to use controlled tier EHR data to develop methods for understanding feature biases of symptoms in patients with specific illnesses.
Project Purpose(s)
- Population Health
Scientific Approaches
Using EHR data, we plan to evaluate illnesses, potentially chronic illnesses like hypertension, and the symptoms reported by patients. Once we are able to evaluate the type of data in the all of us system, we will be able to expand on this section further.
Anticipated Findings
We are unsure, but we can hypothesize that we will see differences in symptoms reported for some illnesses between men and women.
Demographic Categories of Interest
- Race / Ethnicity
- Age
- Sex at Birth
Data Set Used
Controlled TierWearables and Pregnancy
Scientific Questions Being Studied
We are exploring how physiological data collected via wearable devices varies before pregnancy onset, through pregnancy, and following labor.
Project Purpose(s)
- Disease Focused Research (Pregnancy)
Scientific Approaches
We plan to extract data for individuals who have reported pregnancy and shared wearable device data. If minute-level data is available, we will be exploring the effects that pregnancy stage has on circadian rhythms.
Anticipated Findings
We hypothesize that the circadian rhythms of different data modalities change with pregnancy state.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierDuplicate of Demo - Systemic Disease and Glaucoma
Scientific Questions Being Studied
Copy of Demonstration project to understand formatting for a future AoU publication
Project Purpose(s)
- Educational
- Other Purpose (Copy of Demonstration project to understand formatting for a future AoU publication )
Scientific Approaches
Copy of Demonstration project to understand formatting for a future AoU publication
Anticipated Findings
Copy of Demonstration project to understand formatting for a future AoU publication
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierDuplicate of AMIA Genomics Walkthrough
Scientific Questions Being Studied
This workspace is intended to provide basic instruction for using genomics data in All of Us, including cohort identification, covariate extraction, analysis, and display of results. From AMIA 2021 conference
Project Purpose(s)
- Educational
Scientific Approaches
We use OMOP, the cohort builder, and Hail for genomics analysis. The approach will be a simple rule based algorithm along with some open access genomic data to simulate a GWAS.
Anticipated Findings
We do not anticipate any findings as the analysis will not be real. Therefore this will not contribute to scientific knowledge, but hopefully will contribute to individual user's knowledge.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierResearch Team
Owner:
- Lauryn Bruce - Graduate Trainee, University of California, San Diego
Collaborators:
- Jihoon Kim - Project Personnel, University of California, San Diego
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