Product details

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Published by: Stanford Business School
Originally published in: 2020
Version: 28 July 2020

Abstract

Verily Life Sciences, an independent subsidiary of Alphabet, Inc, set out to harness machine learning in the health care field. The company sought partnerships with academic research institutions, legacy life sciences companies, and hospitals and health systems to develop tools to collect and organize health data, with the goal of creating platforms that utilized the insights from that data to enhance patient care. The case study discusses these broad partnerships and goals, the illness-specific health monitoring and care tools in Verily's project pipeline, and efforts by competitors like Apple and Amazon as well as a growing number of start-ups. The case provides insights into decision making in the largely uncharted territory of machine learning in the health care industry, providing an in-depth look at Verily's diabetic retinopathy project, which screened for eye disease.

Time period

The events covered by this case took place in 2020.

Geographical setting

Region:
Americas
Country:
United States

About

Abstract

Verily Life Sciences, an independent subsidiary of Alphabet, Inc, set out to harness machine learning in the health care field. The company sought partnerships with academic research institutions, legacy life sciences companies, and hospitals and health systems to develop tools to collect and organize health data, with the goal of creating platforms that utilized the insights from that data to enhance patient care. The case study discusses these broad partnerships and goals, the illness-specific health monitoring and care tools in Verily's project pipeline, and efforts by competitors like Apple and Amazon as well as a growing number of start-ups. The case provides insights into decision making in the largely uncharted territory of machine learning in the health care industry, providing an in-depth look at Verily's diabetic retinopathy project, which screened for eye disease.

Settings

Time period

The events covered by this case took place in 2020.

Geographical setting

Region:
Americas
Country:
United States

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