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Into the Black Box: What Can Machine Learning Offer Environmental Health Research?

Press/Media: Newspaper Article

Description

AI is becoming a powerful research tool in environmental health. “I see it as a catalyst for innovation within the environmental health sciences that can help us address many unsolved challenges around how best to utilize large and complex data sets,” says Rick Woychik, acting director of the National Institute of Environmental Health Sciences (NIEHS). “Ideally, AI can help us propose new hypotheses or come up with effective solutions for difficult problems.”

Environmental health scientists are already using AI to search the literature for useful information, model the effects of pollutants in cells and tissues, and assess air quality on the basis of remote sensing data. According to Nicole Kleinstreuer, acting director of the National Toxicology Program (NTP) Interagency Center for the Evaluation of Alternative Toxicological Methods, AI could eventually play a critical role in transcriptomic studies of cells’ protein-making machinery and assessments of the “exposome,” or totality of an individual’s chemical exposures over a lifetime.

Period26/02/2020

AI is becoming a powerful research tool in environmental health. “I see it as a catalyst for innovation within the environmental health sciences that can help us address many unsolved challenges around how best to utilize large and complex data sets,” says Rick Woychik, acting director of the National Institute of Environmental Health Sciences (NIEHS). “Ideally, AI can help us propose new hypotheses or come up with effective solutions for difficult problems.”

Environmental health scientists are already using AI to search the literature for useful information, model the effects of pollutants in cells and tissues, and assess air quality on the basis of remote sensing data. According to Nicole Kleinstreuer, acting director of the National Toxicology Program (NTP) Interagency Center for the Evaluation of Alternative Toxicological Methods, AI could eventually play a critical role in transcriptomic studies of cells’ protein-making machinery and assessments of the “exposome,” or totality of an individual’s chemical exposures over a lifetime.

References

TitleInto the Black Box: What Can Machine Learning Offer Environmental Health Research?
Degree of recognitionInternational
Media name/outletEnvironmental Health Perspectives
Media typePrint
Duration/Length/Size5 pages
CountryUnited States
Date26/02/20
DescriptionNow AI is becoming a powerful research tool in environmental health. “I see it as a catalyst for innovation within the environmental health sciences that can help us address many unsolved challenges around how best to utilize large and complex data sets,” says Rick Woychik, acting director of the National Institute of Environmental Health Sciences (NIEHS). “Ideally, AI can help us propose new hypotheses or come up with effective solutions for difficult problems.”

Environmental health scientists are already using AI to search the literature for useful information, model the effects of pollutants in cells and tissues, and assess air quality on the basis of remote sensing data. According to Nicole Kleinstreuer, acting director of the National Toxicology Program (NTP) Interagency Center for the Evaluation of Alternative Toxicological Methods, AI could eventually play a critical role in transcriptomic studies of cells’ protein-making machinery and assessments of the “exposome,” or totality of an individual’s chemical exposures over a lifetime.
Producer/AuthorUS NIEHS
PersonsPaul Whaley, Crispin Halsall