Exploratory Data Analysis to Detect Preterm Risk Factors.
Year: 1997
Type: article
Abstract: This poster is a progress report of a project to mine a computerized patient record for new medical knowledge in perinatal health care. Preterm birth is responsible for a majority of the morbidity and mortality associated with the perinatal period of infants in the United States. Early identification of women at risk for preterm birth allows for pharmacologic and behavioral interventions that attempt to prolong gestation. Unfortunately, current risk assessment scoring tools are only 17 to 38% accurate in correctly predicting preterm birth.' The inadequacy of current risk scoring tools and preterm birth prevention programs likely stems from a failure to fully identify factors that cause preterm birth. The hypothesis of our project is that novel approaches to data analysis applied to an extensive clinical database will detect previously unrecognized factors that contribute to preterm birth. Identification of these factors will significantly improve the ability to identify mothers at risk for preterm delivery. Early and accurate identification of these mothers will allow interventions to be targeted at women with the greatest risk for preterm delivery.
Source: Europe PMC (PubMed Central)
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W1928309375