To date, there is no comprehensive evidence base that captures the breadth of the literature on this topic. To fill this gap, this article uses machine learning methods to systematically synthesize an evidence base on climate change and human health.
The findings show the importance of using automated machine learning to comprehensively map the science on climate change and human health in the age of big literature. These results can provide key inputs into global climate and health assessments.
