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Abstract 178: Predicting Employee Health and Cost: Application of Machine Learning on Employee Health Claims Data, Insights, and Possibilities
Journal article   Peer reviewed

Abstract 178: Predicting Employee Health and Cost: Application of Machine Learning on Employee Health Claims Data, Insights, and Possibilities

Anshul Saxena, Sankalp Das, Muni Rubens, Joseph A Salami, Chintan Bhatt, Tian Tian, Peter McGranaghan, Louis Gidel and Emir Veledar
Circulation: Cardiovascular Quality and Outcomes, Vol.12
2019
DOI: https://doi.org/10.1161/hcq.12.suppl_1.178

Abstract

Background: Self-insured employers, which are majority in US, face an increasing financial burden as health care costs have increased relative to savings. By applying machine learning (ML) techniqu...
url
https://lens.org/113-726-229-536-066View
url
https://www.ahajournals.org/doi/10.1161/hcq.12.suppl_1.178View
url
https://scholarlycommons.baptisthealth.net/se-all-publications/3518/View
url
https://works.bepress.com/sankalp-das/64/View

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