PubAg

Main content area

Using machine learning to examine the relationship between asthma and absenteeism

Author:
Lary, Maria-Anna, Allsopp, Leslie, Lary, David J., Sterling, David A.
Source:
Environmental monitoring and assessment 2019 v.191 no.Supplement 2 pp. 332
ISSN:
0167-6369
Subject:
artificial intelligence, asthma, public health, students
Abstract:
In this study, we found that machine learning was able to effectively estimate student learning outcomes geo-spatially across all the campuses in a large, urban, independent school district. The machine learning showed that key factors in estimating the student learning outcomes included the number of days students were absent from school. In turn, one of the most important factors in estimating the number of days a student was absent was whether or not the student had asthma. This highlights the importance of environmental public health for student learning outcomes.
Agid:
6487635