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Leveraging Machine Learning to Predict Toxicity
Manage episode 321733041 series 3017470
Innhold levert av Adeline Lopez and NIEHS Superfund Research Program. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Adeline Lopez and NIEHS Superfund Research Program eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.
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.
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