Estimating Prevalence, Demographics, and Costs of ME/CFS Using Large Scale Medical Claims Data and Machine Learning

Techniques of data mining and machine learning were applied to a large database of medical and facility claims from commercially insured patients to determine the prevalence, gender demographics, and costs for individuals with provider-assigned diagnosis codes for myalgic encephalomyelitis (ME) or c...

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Bibliographic Details
Published in:Front Pediatr
Main Authors: Valdez, Ashley R., Hancock, Elizabeth E., Adebayo, Seyi, Kiernicki, David J., Proskauer, Daniel, Attewell, John R., Bateman, Lucinda, DeMaria, Alfred, Lapp, Charles W., Rowe, Peter C., Proskauer, Charmian
Format: Artigo
Language:Inglês
Published: Frontiers Media S.A. 2019
Subjects:
Pediatrics
Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC6331450/
https://ncbi.nlm.nih.gov/pubmed/30671425
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fped.2018.00412
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