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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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| 出版年: | Front Pediatr |
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| 主要な著者: | , , , , , , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Frontiers Media S.A.
2019
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| 主題: | |
| オンライン･アクセス: | 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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