Machine Intelligence (MI) is rapidly becoming key to biomedical discovery, clinical research, medical diagnostics and devices, and precision medicine. 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. MI tools can uncover new possibilities for both physicians and patients, allowing them to make more informed decisions and achieve better medical outcomes. When deployed, these outputs can enhance efficiency at every level of the healthcare system.

Meeting Goals
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 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?

We are inviting the community to share their perspectives with us on current issues associated with incorporation of MI tools into healthcare. 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.

This workshop is hosted by the National Center for Advancing Translational Sciences, along with the National Institute of Biomedical Imaging and Bioengineering and the National Cancer Institute.