Artificial Intelligence Research

UH Radiology has been at the forefront of Artificial Intelligence and has implemented AI tools into our daily clinical care. Below are some of our current initiatives:

GE Healthcare

UH Department of Radiology implemented two AI tools for automated endotracheal tube detection and the Critical Care Suite with pneumothorax on the clinical PACS system. In collaboration with GE Healthcare, UH was the first site in the US to implement these improvements in the healthcare system. We continue to work in partnership with GE on multiple AI projects expanding overall patient populations.

Learn more by reading "General Electric Healthcare Chooses UH to Clinically Evaluate First-of-its-kind Imaging System".

AzMed

UH Department of Radiology is currently collaborating with AzMed on a blinded reader study and software evaluation. Rayvolve is a computer-aided diagnosis tool using deep learning and intended to help radiologists and emergency physicians detect and localize fractures on trauma x-rays in regions of the body.

TriNetx

UH Department of Radiology was one of the three sites chosen to help pilot and provide feedback on the radiology clinical notes integration. Currently, the system does not allow queries for radiology clinical notes. We give feedback to the TriNetX operations leadership team to help finalize the process and help start the integration.

Siemens Healthineers

In collaboration with Siemens Heathineers, UH Radiology supports implementing the Integrated Decision Support (“IDS”) system, referred to as AI Pathway Companion Breast Cancer.

Research Team

• Navid Faraji, MD
• Robert Gilkeson, MD
• Amit Gupta, MD
• Leonardo Kayat Bittencourt, MD