Data mining issues for improved birth outcomes.

Journal Article (Journal Article)

Issues obstructing progress in data mining for improved health outcomes include data quality problems, data redundancy, data inconsistency, repeated measures, temporal (time-contextual) measures, and data volume. Related issues involve theoretical and technical problems involving uncertainty management, missing data and missing values, and matching appropriate data mining techniques to patient data sets. Results of data mining research in progress are reported for Duke University's perinatal database that contains nearly a decade of clinical patient data, 71,753 database (patient) records and 4-5000 variables per patient.

Full Text

Duke Authors

Cited Authors

  • Goodwin, L; Prather, J; Schlitz, K; Iannacchione, MA; Hage, M; Hammond, WE; Grzymala-Busse, J

Published Date

  • 1997

Published In

Volume / Issue

  • 34 /

Start / End Page

  • 291 - 296

PubMed ID

  • 9603055

International Standard Serial Number (ISSN)

  • 0067-8856


  • eng

Conference Location

  • United States