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How This Startup Is Using 10 Million Patient Records To Reduce Bias In Healthcare AI

Dec 21, 2023 - forbes.com
Dandelion Health, a startup co-founded by Ziad Obermeyer, is working on creating a massive, de-identified dataset from millions of patient records to help developers build and test healthcare algorithms for potential bias. The company aims to fill the gap left by the slow pace of regulatory development in the rapidly advancing field of AI in healthcare. Dandelion recently closed a $15 million seed round and has partnered with three hospitals to create a dataset from the medical records of 10 million patients.

The startup's goal is to help establish a framework for testing and validating healthcare AI while regulators catch up. It plans to create a marketplace where algorithms that have been tested and validated on its data will be connected with health systems and other customers. The company's efforts are in response to the issue of bias in healthcare algorithms, which can result in inaccurate predictions and diagnoses for certain patient groups.

Key takeaways:

  • Dandelion Health is a startup that is creating a massive, de-identified dataset from millions of patient records to help developers build and test the performance of their healthcare algorithms across diverse types of patients.
  • The company recently closed a $15 million seed round and has partnerships with three hospitals to take the medical records of 10 million patients.
  • One of the main challenges in developing health-related algorithms is the lack of representative data, which can lead to bias and performance problems.
  • Dandelion Health's goal is to provide a solution to this problem and establish a framework for testing and validating healthcare AI while regulators are still catching up with the rapidly evolving technology.
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