A systematic review of data mining and machine learning for air pollution epidemiology
BACKGROUND: Data measuring airborne pollutants, public health and environmental factors are increasingly being stored and merged. These big datasets offer great potential, but also challenge traditional epidemiological methods. This has motivated the exploration of alternative methods to make predictions, find patterns and extract information. To this end, data mining and machine learning algorithms are increasingly being applied to air pollution epidemiology. METHODS: We conducted a systematic
Record details
Published: 28 November 2017
Source: OpenAlex
Category: Research
Topics: Healthcare · Environment
Retrieved: 14 July 2026
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How to cite this record
ethics.ai (28 November 2017), “A systematic review of data mining and machine learning for air pollution epidemiology,” evidence record 8128, https://ethics.ai/record/8128 (originally published by OpenAlex).
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