Working with Health Data

Workshop Title:  Working with health data: responsibilities, opportunities, and the AI-READI dataset

Presenters: Jamie Shaffer, Research Scientist, Julia Owen, Senior Research Scientist, University of Washington School of Medicine, Lee Lab for Computational Ophthalmology

Abstract:

AI has the potential to transform our understanding of health and healthcare and there are many opportunities to leverage its capabilities. At the same time, there are important legal considerations for handling health data and failure to comply can be very costly. This workshop will introduce the legal landscape affecting health datasets, help data scientists understand their responsibilities and avoid legal and ethical issues, and tie all of this together with an introduction to accessing and working with the multimodal “Artificial Intelligence Ready and Equitable Atlas for Diabetes Insights” (AI-READI) pilot dataset released in May 2024.

Hands-on:

No, although attendees may navigate to the aireadi.org website on any wifi connected device and get started learning about it.

Attendees:

Most information is suitable to any audience; some information will be more suited to those who build or train machine learning models

Takeaways

  1. High level understanding of the legal constraints when working with health data
  2. Overview of methods and tools to consider when working with health data
  3. Introduction to the AI-READI dataset including how to access it

Presenter Bios:

Jamie Shaffer, Research Scientist, University of Washington School of Medicine, Lee Lab for Computational Ophthalmology

Jamie Shaffer earned a BSEE from Michigan State University and an MSEE from the University of Washington. Her background includes research and development in novel image sensors, imaging systems, and image-based metrology. In 2020, she pivoted to a career in data science, joining the Lee Lab for Computational Ophthalmology at the University of Washington where her interests include data analysis and applying deep learning to challenges in medical imaging.

 

Julia Owen, Senior Research Scientist, University of Washington School of Medicine, Lee Lab for Computational Ophthalmology

Julia Owen was raised in the DC suburbs. She joined the Lee Lab in 2019. Her scientific interests include medical imaging, deep learning, and big data analysis. She was previously a postdoctoral fellow focusing on diffusion MRI and fMRI-related studies of different neurological diseases at UCSF. More recently, she was a Research Scientist at the Integrated Brain Imaging Center at the University of Washington.