I have been interested in computers and their capability to solve problems since high school when I started writing software for electrophoresis analysis using the Apple II I had been using for gaming. I've been involved with digital pathology since finishing medical school. After growing a company focused on digitizing pathology slides, which was ultimately acquired by Carl Zeiss, the utilization and complete harvesting of the information contained in those images became a clear next step. I believe that Artificial Intelligence is the key to unlocking the potential of this vast trove of data contained in Pathology slides, PreciseDx, was borne out of this belief. AI is the cornerstone of our technology.

Diagnosing Parkinson's disease is challenging at all stages due to variable symptoms, comorbidities, and mimicking conditions, with definitive diagnosis only coming postmortem. This groundbreaking study found that PreciseDx's AI-enabled technology is able to facilitate a conclusive diagnosis of Parkinson's, providing critical information for earlier treatment. PreciseDx's AI Morphology Feature Array was able to detect Parkinson's pathology in image patches from biopsy samples with 99% sensitivity and 99% specificity as compared to expert annotated ground truth. The AI edged out the human pathologist with an accuracy of 0.69 versus 0.64 in the prediction of clinical Parkinson's disease status. PreciseDx's MFA approach to feature extraction and analysis enables new algorithms to be developed and validated against clinical endpoints.