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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.

United statesStephanie cookRumi chunaraEmily hendersonYork university school of global public healthTandon school of engineeringSchool of global public healthNew york universityGlobal public healthTandon schoolAmerican journalPreventive medicineஒன்றுபட்டது மாநிலங்களில்மாற்றாந்தாய் சமைக்கவும்ரூமி சுனாராஎமிலி ஹென்டர்சன்