商品敘述：

An Israeli startup founded in 2014, Zebra Medical Vision, develops 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 decide: 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?

涵蓋領域：

Analytics;Commercialization;Competitive strategy;Decision making;Entrepreneurship;Machine-based learning;Marketing;Operations and processes;Organizational learning;Probability;Product development;Strategy;Technology

相關資料：

Case Teaching Note, (5-619-053), 12p, by Shane Greenstein, Sarah Gulick

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