UVU Students Build $400 AI Device That Detects Knee Implant Infection Without Surgery
Carter Wilkes, a Physics undergraduate at Utah Valley University, has developed DIFFRAX
— a laser-and-AI diagnostic device that detects bacterial infection in knee implants
without surgery. Built from repurposed 3D printer parts and off-the-shelf components
for under $400, the device achieves 99.2 percent accuracy in approximately five minutes,
without a single incision.
Working in UVU's CIBEAM lab under faculty advisor Dr. Vern Hart, Wilkes trained a
neural network to identify bacterial biofilm patterns invisible to the human eye.
The research was presented at the 32nd Annual Utah NASA Space Grant Consortium Fellowship
Symposium.
Read full article at TechBuzz News
