Dr. Devin Singh

Our project has the ability to completely revolutionize ocular assessments at scale given the prevalent use of inadequate ophthalmoscopes in clinical practice.

Nearly every ED room, inpatient ward room, and community practice offices have traditional ophthalmoscopes mounted to the walls highlighting the broad need for performing fundoscopy in patients. These devices are expensive and ineffective at facilitating assessments for papilledema when used by primary care physicians. In addition, the findings from direct manual visualization of the eye (fundoscopy) cannot be saved and shared with other healthcare providers.

By harmonizing machine learning with well-established ocular POCUS techniques, our project will demonstrate how AI can elevate already existing technologies to solve complex system-wide health problems.

Clinically, this will enable more accurate assessments in urban, community, and rural settings and better standardize how raised ICP is detected in children. Impact on remote locations is particularly powerful by helping triage who should be transported from “fly-in” communities for neuroimaging.

Our future vision is to distribute our solution via commercially available portable ultrasound machines, integrate into a standalone device, and create a web-based application for uploading ocular POCUS scans. Our applications can also scale easily to adult populations in the future as the anatomy is nearly identical.