Bradley Merrill Thompson, Strategic Advisor with EBG Advisors and Member of the Firm at Epstein Becker Green, co-authored a whitepaper titled “Data Quality for AI in Healthcare,” a collaborative piece developed under the leadership of the Xavier Health program at Xavier University in partnership with industry professionals.

Following is an excerpt:

Over the past few years, Artificial Intelligence (AI), and more specifically Machine Learning (ML) technology has experienced rapid adoption in the healthcare space as tools for diagnosis and decision-making. Such tools are intended to address challenges in the health care system to both process and the application of rapidly proliferating medical findings to practice, as well as to deliver on the promise of personalized and precision medicine.

The classic computer science idiom of “garbage in = garbage out” certainly holds true for ML systems; the quality of the data used to develop and test the system has a significant impact on the quality of the system output. There are many examples in the press where poor data quality led to poor recommendations and even led to instances of discrimination against certain patient populations, due to bias in the data that was used to develop the system. This paper, developed by the Xavier GMLP (Good Machine Learning Practices) Working Team, attempts to describe and address these potential data quality issues.

Learn more about new learnings and best practices in AI in health care by downloading the free whitepaper.

Jump to Page

Privacy Preference Center

When you visit any website, it may store or retrieve information on your browser, mostly in the form of cookies. This information might be about you, your preferences or your device and is mostly used to make the site work as you expect it to. The information does not usually directly identify you, but it can give you a more personalized web experience. Because we respect your right to privacy, you can choose not to allow some types of cookies. Click on the different category headings to find out more and change our default settings. However, blocking some types of cookies may impact your experience of the site and the services we are able to offer.

Strictly Necessary Cookies

These cookies are necessary for the website to function and cannot be switched off in our systems. They are usually only set in response to actions made by you which amount to a request for services, such as setting your privacy preferences, logging in or filling in forms. You can set your browser to block or alert you about these cookies, but some parts of the site will not then work. These cookies do not store any personally identifiable information.

Performance Cookies

These cookies allow us to count visits and traffic sources so we can measure and improve the performance of our site. They help us to know which pages are the most and least popular and see how visitors move around the site. All information these cookies collect is aggregated and therefore anonymous. If you do not allow these cookies we will not know when you have visited our site, and will not be able to monitor its performance.