Skip to content
Leveraging Machine Learning to Predict Toxicity episode artwork

Mar 2, 2022 4 min

Leveraging Machine Learning to Predict Toxicity

from NIEHS Superfund Research Program - Research Brief Podcasts Hosted by Superfund Research Program

NIEHS Superfund Research Program (SRP) grantees developed a new computational approach to predict how hazardous substances may affect health based on key changes in cells. Led by April Z. Gu, Ph.D., of the Northeastern University Puerto Rico Testsite for Exploring Contamination Threats (PROTECT) SRP Center, researchers used machine learning and advanced algorithms to link biological changes from high throughput cell studies with health outcomes observed in animal studies.

Episode details come from the podcast's RSS feed.

Embed this episode

Ready to play

Leveraging Machine Learning to Predict Toxicity

0:00 4:48

No transcript yet.

Requests help us decide what to transcribe next.

Frequently asked questions

How long is this episode of NIEHS Superfund Research Program - Research Brief Podcasts?

This episode is 4 minutes long.

When was this NIEHS Superfund Research Program - Research Brief Podcasts episode published?

This episode was published on March 2, 2022.

Can I download this NIEHS Superfund Research Program - Research Brief Podcasts episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.