There is a number of undergraduate students who may be able to assist with various AI/ML projects within the translational data analytics program. These students have varying specialties: biomedical informatics, computational analysis and data visualization (for more information) These students are not necessarily required to be paid; however if faculty have funding to provide, that would be favorable but not required.

For more information, please contact Brooke O’Leary (Oleary.158@osu.edu) and Srini Parthasarathy (srini@cse.ohio-state.edu or Parthasarathy.2@osu.edu).

The 2019 CCTS Artificial Intelligence Request for Applications

To gather perspectives on current issues associated with the incorporation of Machine Intelligence (MI) systems into healthcare settings, NCATS, the National Cancer Institute and the National Institute of Biomedical Imaging and Bioengineering co-hosted a workshop in July 2019. The resulting white paper publication is now available.

Workshop attendees—who represented industry, academia, patients and federal agencies—addressed the following issues and many others:

• Data quality and quantity 
• Access and use of electronic health records
• Transparency and explainability of the system in contrast to the entire clinical workflow
• Impact of bias on system outputs

The white paper, published today in Nature’s Digital Medicine, covers key issues associated with MI specific to applications in the healthcare field and potential avenues and solutions to address them. If appropriately addressed, such solutions could accelerate progress in the field in an effective, transparent and ethical manner.

Read the white paper and learn more about applying MI in clinical care settings.