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Improving automated case finding for ectopic pregnancy using a classification algorithm.

D Scholes1, O Yu, M A Raebel

  • 1Group Health Research Institute, Group Health Cooperative, 1730 Minor Ave., 16th floor, Seattle, WA 98101, USA. scholes.d@ghc.org

Human Reproduction (Oxford, England)
|September 14, 2011
PubMed
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This summary is machine-generated.

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An improved algorithm using automated health data significantly enhances ectopic pregnancy case identification accuracy compared to standard diagnostic codes alone. This method offers better surveillance for ectopic pregnancy.

Failed At:

2026-06-19T13:36:41.885741+00:00

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