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New Model Helps Decide About Easing COVID-19 Restrictions

New Model Helps Decide About Easing COVID-19 Restrictions
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Ruth Pearl, Mother of Murdered Reporter Daniel Pearl, Dies at 85

Ruth Pearl, Mother of Murdered Reporter Daniel Pearl, Dies at 85
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Research infuses equity principles into algorithm development process

Research infuses equity principles into algorithm development process
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Machine learning models that include social determinants of health better predict cardiovascular outcomes

Machine learning models that include social determinants of health better predict cardiovascular outcomes
Machine learning can accurately predict cardiovascular disease and guide treatment--but models that incorporate social determinants of health better capture risk and outcomes for diverse groups, finds a new study by researchers at New York University's School of Global Public Health and Tandon School of Engineering. The article, published in the
American Journal of Preventive Medicine, also points to opportunities to improve how social and environmental variables are factored into machine learning algorithms.
Cardiovascular disease is responsible for nearly a third of all deaths worldwide and disproportionately affects lower socioeconomic groups. Increases in cardiovascular disease and deaths are attributed, in part, to social and environmental conditions--also known as social determinants of health--that influence diet and exercise.

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New York University: Machine Learning for Cardiovascular Disease Improves When Social, Environmental Factors Are Included

New York University: Machine Learning for Cardiovascular Disease Improves When Social, Environmental Factors Are Included
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Machine Learning for Cardiovascular Disease Improves When Social, Environmental Factors Are Included

Machine Learning for Cardiovascular Disease Improves When Social, Environmental Factors Are Included
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Machine learning for cardiovascular disease improves when social, environmental factors included: Study

Machine learning for cardiovascular disease improves when social, environmental factors included: Study
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Study on machine learning for cardiovascular disease

Study on machine learning for cardiovascular disease
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Novel research revealing how a unique sponge goes with the flow could improve man-made structures

Novel research revealing how a unique sponge goes with the flow could improve man-made structures
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How a unique sponge 'goes with the flow' could improve man-made structures

E-Mail
BROOKLYN, New York, Weekday, Month xx, 2021 - The remarkable structural properties of the Venus' flower basket sponge (E. aspergillum) might seem fathoms removed from human-engineered structures. However, insights into how the organism's latticework of holes and ridges influences the hydrodynamics of seawater in its vicinity could lead to advanced designs for buildings, bridges, marine vehicles and aircraft, and anything that must respond safely to forces imposed by the flow of air or water.
While past research has investigated the structure of the sponge, there have been few studies of the hydrodynamic fields surrounding and penetrating the organism, and whether, besides improving its mechanical properties, the skeletal motifs of E. Aspergillum underlie the optimization of the flow physics within and beyond its body cavity.

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