Registration Open – NIH/NCATS Workshop

Friday, June 14, 2019

"Machine Intelligence in Healthcare: Perspectives on Trustworthiness, Explainability, Usability and Transparency": July 12

Registration is now open for the NIH/NCATS Workshop “Machine Intelligence in Healthcare: Perspectives on Trustworthiness, Explainability, Usability and Transparency” to be held on July 12, 2019 at the Neuroscience Center, National Institutes of Health, 6001 Executive Blvd, Rockville, Maryland 20852. 

This workshop is sponsored by the National Institutes of Health (NIH) National Center for Advancing Translational Sciences (NCATS) and has been organized jointly with the National Institute of Biomedical Imaging and Bioengineering (NIBIB) and the National Cancer Institute (NCI).

We are inviting members of the extramural scientific community, government agencies, health care providers, industry and the public to share their perspectives with us on current issues associated with incorporation of machine intelligence (MI) tools into healthcare. In the context of this meeting, MI is defined as the ability of a trained computer system to provide rational, unbiased guidance to humans in such a way that achieves optimal outcomes in a range of environments and circumstances. Meeting outputs from this workshop will be used to develop a whitepaper on translating MI for clinical applications and the associated process improvement needed when implementing MI tools in healthcare environments.

We are interested in exploring current issues associated with incorporation of MI tools into healthcare.  As such, we are primarily aiming to expand our knowledge in the following areas:

  1. How can we better stimulate data sharing and open access to training data/MI algorithm development?
  2. How can we identify and prevent bias in MI healthcare tools?
  3. How should we address quality control and use of standards?
  4. What tools are needed to ensure usability of MI systems in multiple environments?
  5. What tools are needed to evaluate MI output reliability and safety?
  6. What methods would allow for introduction of data updates to MI systems without altering trustworthiness of outputs?
  7. What lessons have already been learned?

Registration is free but seating is limited, so be sure to register early to ensure that your seat is reserved.   If you are a member of a lab or group who plans to attend, please limit your group to 1-2 in-person attendees in order to assure that there will be enough seats for everyone who would like to attend.  If you register, but find that you are unable to attend, please notify Cara Lynch ( so that we may open up your seat to additional attendees.    

For those unable to attend in person, the meeting will also be videocast live.  Access to the videocast can be obtained by registering at the link below and selecting “videocast”.

Registration (In person and videocast) is closed.

This page last reviewed on June 3, 2024