Clinical AI and Clinical Informatics in the Apollo Hospitals Network, India

Sujoy Kar, MD, is the Chief Medical Information Officer & Vice President, Apollo Hospitals Group. The Apollo Hospitals Group is India’s largest Health Care Network with over 70 hospitals. Kar is a distinguished Clinical AI leader with over two decades of experience in healthcare quality, digital transformation, and large-scale deployment of Clinical and Generative AI. He currently leads the design, development, certification, and global deployment of AI-driven clinical and operational solutions across Apollo Hospitals and partner ecosystems.

Event Location:322 Macnider Hall, UNC School of Medicine

In this session, participants will have the opportunity to ask questions and seek feedback on their qualitative analyses from facilitators and other attendees. This session serves as a workshop in which participants get a chance to discuss and review qualitative analysis techniques while also learning from others.

Please note: We will not be presenting information about qualitative analysis in this session; instead, we will ask participants to share where they are in their analysis process, ask questions about their analyses, and collectively discuss strategies for moving our analyses forward. This event will not be recorded.

Facilitators:
MaryBeth Grewe, MPH
Program Manager, Qualitative Research Service
Research Specialist, Patient and Community Engagement in Research (PaCER) Program

Simone Frank, MPH
Senior Project Manager, Patient and Community Engagement in Research (PaCER) Program
Research Specialist, Qualitative Research Service

Sharita Thomas, MPP
Research Specialist, Qualitative Research Service

For questions about this workshop, please contact MaryBeth Grewe at This email address is being protected from spambots. You need JavaScript enabled to view it..

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Tools, Technology and Teamwork: How NCDRC Cores Support Diabetes Research

Join the North Carolina Diabetes Research Center (NCDRC) for a virtual overview of their core offerings.

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Join us for a laptop-optional workshop to learn more about statistical power, the relationship of statistical power to study design, and how to design a simulation study to assess power. Code samples will be provided in both R and Python.

In this workshop, you will learn how to:

• Define statistical power as a concept
• Understand how power calculations relate to study design
• Learn to design a simulation study to assess power

Workshop outline:

1. Welcome and introduction
    a. Define statistical power in the context of null hypothesis significance testing

2. Overview of power calculations
    a. Why calculate power?
    b. What impacts power?
    c. Why is power meaningful?

3. Introduction to simulation studies for power
    a. Precision
    b. Two-group comparison
    c. Three-group comparison
    d. Correlation

4. Conclusions/next steps
    a. Detecting and avoiding common mistakes

Prerequisites
You should be able to do these things in either R or Python: 

• Write, save, and execute code
• Make simple visualizations

Statistical challenges in Long COVID research: Ongoing lessons from the RECOVER observational cohort

Long COVID, also known as postacute sequelae of SARS-CoV-2 infection (PASC), is a chronic condition characterized by long-term symptoms that persist for months or even years after initial SARS-CoV-2 infection. Over 200 symptoms have been identified as being associated with Long COVID, affecting nearly every body system. Long COVID is known to manifest differently across individuals, wax and wane over time, and range from mild to incapacitating, with profound effects on quality of life. While recognition of Long COVID is growing among adults, it is still woefully understudied in children.

The rapid materialization of large-scale observational data, including the Researching COVID to Enhance Recovery (RECOVER) meta-cohort, has generated enormous opportunity for novel discovery that could lead to effective prevention strategies and improved outcomes for patients living with Long COVID. The statistical challenges inherent in effectively and appropriately leveraging these novel data resources are numerous. In this talk, the lead biostatistician of the Data Resource Core for RECOVER will present their work developing a working definition for a new chronic disease, and highlight the many statistical challenges in the study of Long COVID.

Speaker:
Tony Thaweethai, PhD
Associate Director of Collaborative Research and Educational Initiatives,
Massachusetts General Hospital Biostatistics
Assistant Professor of Medicine,
Harvard Medical School

This event is being cross-promoted by the NC BERD Consortium, a collaboration of the CTSA-funded BERD cores at UNC-Chapel Hill, Wake Forest University School of Medicine, and Duke University School of Medicine.