Mark Weiner
Mid-career Tenured Researcher, Cornell University
4 active projects
V7 PASC Workspace
Scientific Questions Being Studied
This project will explore the scope of patients with COVID-19 and the characteristics of patients with PASC.
Project Purpose(s)
- Educational
- Ancestry
- Other Purpose (practice notebook to familiarize with RW)
Scientific Approaches
We will apply algorithms developed by the RECOVER PCORnet Adult Cohort and compare the overlap in cohorts with the set derived though the N3C algorithm
Anticipated Findings
We expect to find a high degree of concordance between the RECOVER Adult Cohort algorithm and the N3C algorithm, even though the approaches were developed through different machine learning methods on different source patient data sets
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierResearch Team
Owner:
- Srushti Gangireddy - Project Personnel, Vanderbilt University Medical Center
- Mark Weiner - Mid-career Tenured Researcher, Cornell University
- Hiral Master - Project Personnel, All of Us Program Operational Use
- Aashri Aggarwal - Undergraduate Student, Cornell University
Practice Notebook to Explore AoU dataset
Scientific Questions Being Studied
This project will explore the scope of patients with COVID-19 and the characteristics of patients with PASC.
Project Purpose(s)
- Educational
- Other Purpose (practice notebook to familiarize with RW)
Scientific Approaches
We will apply algorithms developed by the RECOVER PCORnet Adult Cohort and compare the overlap in cohorts with the set derived though the N3C algorithm
Anticipated Findings
We expect to find a high degree of concordance between the RECOVER Adult Cohort algorithm and the N3C algorithm, even though the approaches were developed through different machine learning methods on different source patient data sets
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierResearch Team
Owner:
- Srushti Gangireddy - Project Personnel, Vanderbilt University Medical Center
- Mark Weiner - Mid-career Tenured Researcher, Cornell University
- Hiral Master - Project Personnel, All of Us Program Operational Use
Collaborators:
- Aashri Aggarwal - Undergraduate Student, Cornell University
AOU_Recover_Long_Covid_v6
Scientific Questions Being Studied
The purpose of this workspace was to implement the published XGBoost machine learning (ML) model, which was developed using the National COVID Cohort Collaborative’s (N3C) EHR repository to identify potential patients with PASC/Long COVID in All of Us Research Program. N3C, All of Us, PCORnet and RECOVER teams collaborated to execute this purpose to enhance the overall PASC/Long COVID efforts.
Project Purpose(s)
- Disease Focused Research (Long COVID)
Scientific Approaches
To achieve this objective, data science workflows were used to apply ML algorithms on the Researcher Workbench. This effort allowed an expansion in the number of participants used to evaluate the ML models used to identify risk of PASC/Long COVID and also serve to validate the efforts of one team and providing insight to other teams. These models were implemented within the All of Us Controlled Tier data (C2022Q2R2), which was last refreshed on June 22, 2022. We intend to provide a step-by-step guide for the implementation of N3C's ML Model for identification of PASC/Long COVID Phenotype in the All of Us dataset. It also evaluated demographic characteristics for participants who were identified as possibly having PASC/Long COVID, and provides additional details on model performance, such as areas under the receiver operator characteristic curve and confusion matrix.
Anticipated Findings
We intend to provide a step-by-step guide for the implementation of N3C's ML Model for identification of PASC/Long COVID Phenotype in the All of Us dataset. The findings and code use to generate the demographic characteristics for participants who were identified as possibly having PASC/Long COVID, and provides additional details on model performance, such as areas under the receiver operator characteristic curve and confusion matrix.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierResearch Team
Owner:
- WeiQi Wei - Other, All of Us Program Operational Use
- Vern Kerchberger - Early Career Tenure-track Researcher, Vanderbilt University Medical Center
- Srushti Gangireddy - Project Personnel, Vanderbilt University Medical Center
- Mark Weiner - Mid-career Tenured Researcher, Cornell University
- Hiral Master - Project Personnel, All of Us Program Operational Use
- Gabriel Anaya - Administrator, National Heart, Lung, and Blood Institute (NIH - NHLBI)
- David Mohs - Other, All of Us Program Operational Use
- Christopher Lord - Project Personnel, All of Us Program Operational Use
- Chenchal Subraveti - Project Personnel, All of Us Program Operational Use
Collaborators:
- Jun Qian - Other, All of Us Program Operational Use
- Chris Lunt - Other, All of Us Program Operational Use
Duplicate of Duplicate of Phenotype - Ischemic Heart Disease (v6)
Scientific Questions Being Studied
The Notebooks in this workspace can be used to implement well-known phenotype algorithms in one’s own research.
Project Purpose(s)
- Educational
- Methods Development
- Other Purpose (This is an All of Us Phenotype Library Workspace created by the Researcher Workbench Support team. It is meant to demonstrate the implementation of key phenotype algorithms within the All of Us Research Program cohort.)
Scientific Approaches
Not Applicable
Anticipated Findings
By reading and running the Notebooks in this Phenotype Library Workspace, researchers can implement the following phenotype algorithms:
Christianne L. Roumie; Jana Shirey-Rice, Sunil Kripalani. Vanderbilt University. MidSouth CDRN - Coronary Heart Disease Algorithm. PheKB; 2014. Available from https://phekb.org/phenotype/234
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierRequest a Review of this Research Project
You can request that the All of Us Resource Access Board (RAB) review a research purpose description if you have concerns that this research project may stigmatize All of Us participants or violate the Data User Code of Conduct in some other way. To request a review, you must fill in a form, which you can access by selecting ‘request a review’ below.
