作者
Adyasha Maharana, Kunlin Cai, Joseph Hellerstein, Yulin Hswen, Michael Munsell, Valentina Staneva, Miki Verma, Cynthia Vint, Derry Wijaya, Elaine O Nsoesie
发表日期
2019/10
期刊
JAMIA open
卷号
2
期号
3
页码范围
330-338
出版商
Oxford University Press
简介
Objectives
Access to safe and nutritious food is essential for good health. However, food can become unsafe due to contamination with pathogens, chemicals or toxins, or mislabeling of allergens. Illness resulting from the consumption of unsafe foods is a global health problem. Here, we develop a machine learning approach for detecting reports of unsafe food products in consumer product reviews from Amazon.com.
Materials and Methods
We linked Amazon.com food product reviews to Food and Drug Administration (FDA) food recalls from 2012 to 2014 using text matching approaches in a PostGres relational database. We applied machine learning methods and over- and under-sampling methods to the linked data to automate the detection of reports of unsafe food products.
Results
Our data consisted of 1 297 156 product reviews from Amazon.com …
学术搜索中的文章
A Maharana, K Cai, J Hellerstein, Y Hswen, M Munsell… - JAMIA open, 2019