Data Science

If you have ever wanted to code but thought it was too hard to learn, now is a great time to dive in and get started. The international Hour of Code is a global event designed to demystify programming and make it more accessible to people of all ages and backgrounds with several one-hour programming classes. The NIH Library, the National Library of Medicine, and the NIH Data Scientific Interest Group are partnering to host a celebration of the 2017 Hour of Code.

In partnership with the NIH Clinical Center's Biostatistics and Clinical Epidemiology Service (BCES), the NIH Library is offering a review of core concepts in epidemiology. This session will cover the principles of epidemiology, key concepts and terms, brief review of outbreak investigations and study designs, and commonly used statistics in epidemiology (e.g., morbidity and mortality rates; incidence and prevalence; relative risk; odds ratio; sensitivity and specificity).

The National Health and Nutrition Examination Survey (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. NHANES is a major program of the National Center for Health Statistics (NCHS), part of the Centers for Disease Control and Prevention (CDC). This introductory one-hour webinar by Jane Gwira Baumblatt, MD, MPH,  will provide an overview of the content of NHANES and how to access the data. 

Macros are ways to use code to substitute in a value, and using macros makes a code in SAS easier to read and edit, less prone to errors, and allows it to run more efficiently. This 90-minute advanced class will provide an in-depth look at using and writing macros in SAS. Topics covered in this class include macro function, using SQL and Data Step to create macro variables, indirect references to macro variables, defining and calling a macro, macro variable scope, conditional processing, and iterative processing. 

This webinar will include live demonstrations of various Application Programming Interfaces (APIs) and specific use cases.

The live demonstrations of APIs will cover:

• Research assessment
• Policy formation and tracking
• Funding evaluation

A Clarivate instructor will take a deep dive into APIs and share technical examples using APIs, as well as suggest practical methods to apply APIs within your organization.

Large language models (LLMs) are artificial intelligence (AI) algorithms that employ deep learning and extensive data sets to create new content. LLMs offer many possible applications in the biomedical field, such as the development of chatbots for use by clinicians, patients, and researchers. Join this roundtable discussion to learn about current use cases of LLMs at NIH. The program will begin with brief presentations by our panelists, followed by an open discussion:

Alicia Lillich, NIH Library 
Introduction to Large Language Models (LLMs)

This first of five webinars will introduce NIH’s All of Us Research Program, including the program’s mission and core values. Learn about the current size and diversity of the participant cohort and the data types and tools available to researchers. Attendees will also see examples of recent research using the All of Us dataset. 

This session will outline the All of Us Researcher Workbench registration process for NIH researchers. Access to the Researcher Workbench is free, and all registered researchers are provided $300 initial computational credits. Some analyses in the cloud may incur additional costs beyond these credits. Attendees will also learn how to create a Google billing account in case they use up their initial credits. Finally, attendees will hear about funding opportunities that can support using the All of Us dataset. 

In this webinar, attendees will learn the basics of using the All of Us Researcher Workbench’s point-and-click research tools, including how to create a workspace, how to build a cohort of All of Us participants using the Cohort Builder, and more. 

Webinar attendees will hear tips and tricks to code efficiently in the Researcher Workbench using R and RStudio. Although Python and SAS are alternative programming languages available on the Researcher Workbench, this session will only focus on using R and RStudio. Participants should already have a general understanding of how to code in R prior to attending the session. This session will not cover the basics of coding in R.

Webinar attendees will learn how to use and navigate the All of Us Researcher Workbench’s User Support Hub, which provides video tutorials, help articles, and more. Attendees will also learn about opportunities to get support from the Researcher Workbench help desk and how to stay involved with the All of Us Research Program through the program’s network of partners. 

Presenters:

Python is an open-source, object-oriented programming language, particularly well-suited for scientific computing because of its extensive ecosystem of scientific libraries and environments. For more information, see the Python FAQ page and the Python Numeric and Scientific Wiki.