AI-based approach uncovers social patterns that impact child health outcomes

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A research team at Weill Cornell Medicine used artificial intelligence to analyze over 10,500 American children in 17 states and the social determinants of health in their neighborhoods. They found links between certain social factors and child health, such as affluence, high stigma environments, high socioeconomic deprivation, and high crime and drug sale rates. The study was led by Dr. Yunyu Xiao and Dr. Chang Su, experts in using advanced AI techniques for this type of analysis. Their work provides insights into what social factors might influence children’s health, potentially guiding policies for improvement. The researchers call for more targeted studies to investigate the actual causal mechanisms connecting social factors to child health.

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