Case | HBS Case Collection | September 2018 (Revised December 2019)

Zebra Medical Vision

by Shane Greenstein and Sarah Gulick

Abstract

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; Business Startups; Health Care and Treatment; Technology; Software; Competitive Strategy; Product Development; Commercialization; Decision Choices and Conditions; Health Industry; Medical Devices and Supplies Industry; Technology Industry; Israel;

Language: English Format: Print 26 pages EducatorsPurchase

Citation:

Greenstein, Shane, and Sarah Gulick. "Zebra Medical Vision." Harvard Business School Case 619-014, September 2018. (Revised December 2019.)

Related Work

  1. Teaching Note | HBS Case Collection | June 2019

    Zebra Medical Vision

    Shane Greenstein and Sarah Gulick

    Teaching note is meant to accompany Zebra Medical Vision case, which offers a look at a company’s decisions as a small startup competing with other startups and major technology companies. It also demonstrates the challenges faced by a machine learning company working on brand-new technology, including difficulties finding training data, hiring competition, and negotiating FDA approvals and other government regulations. Teaching Note for HBS No. 619-014.

    Keywords: Business Startups; Science-Based Business; Software; Patents; Cross-Cultural and Cross-Border Issues; Health Care and Treatment; Health Industry; Medical Devices and Supplies Industry; Technology Industry; Israel;

    Citation:

    Greenstein, Shane, and Sarah Gulick. "Zebra Medical Vision." Harvard Business School Teaching Note 619-053, June 2019.  View Details
    CiteView DetailsPurchase Related

  2. Case | HBS Case Collection | September 2018 (Revised December 2019)

    Zebra Medical Vision

    Shane Greenstein and Sarah Gulick

    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; Business Startups; Health Care and Treatment; Technology; Software; Competitive Strategy; Product Development; Commercialization; Decision Choices and Conditions; Health Industry; Medical Devices and Supplies Industry; Technology Industry; Israel;

    Citation:

    Greenstein, Shane, and Sarah Gulick. "Zebra Medical Vision." Harvard Business School Case 619-014, September 2018. (Revised December 2019.)  View Details
    CiteView DetailsEducatorsPurchase Related

About the Author

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Shane M. Greenstein
Martin Marshall Professor of Business Administration
Technology and Operations Management

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