An Israeli startup founded in 2014, Zebra Medical Vision developed algorithms that produced diagnoses from X-rays, mammograms, and CT-scans. The algorithms used deep learning and digitized radiology scans to create software that could assist doctors in making diagnoses. By July 2018, Zebra had developed seven algorithms to analyze scans for emphysema, liver density, compression fractures, bone density, brain bleeds, breast cancer, and a calcium score used to detect calcified plaque in coronary arteries. For each scan analyzed, Zebra charged hospitals $1. By 2018 Zebra found itself in a race with its competitors to perfect these algorithms, create software tools, distribute the tools to physician partners, and create a market. Zebra already had several partners in the U.S. and Europe who gave feedback on its development. Management had to answer the following questions: What should they do next at Zebra? Should they work on the accuracy of the already developed algorithms or continue to develop many new tools? If they chose to develop new products, which applications should they address? And how should they go to market?
Keywords: radiology; Machine learning; X-ray; CT scan; medical technology; probability; FDA 510(k); diagnosis; Health Testing and Trials; Technology; Competitive Strategy; Product Development; Commercialization; Decision Choices and Conditions; Israel;
Citation:
Greenstein, Shane, and Sarah Gulick. "Zebra Medical Vision." Harvard Business School Case 619-014, September 2018. (Revised November 2018.) View Details
