A data mining technique for risk-stratification diagnosis.

Chih Lin Chi, W. Nick Street

Research output: Contribution to journalArticlepeer-review

Abstract

We describe a data mining model for sequential diagnosis, called the Optimal Decision Path Finder (ODPF), which is built based on the idea of risk stratification. A filter was used to stratify patients depending on ease of diagnosis, and a series of patient-specific classifiers was built to diagnose with confidence while reducing exam cost. Results show that applying stratification to data mining can improve the diagnostic performance and reduce waste of medical resource. This resulting model can assist the physician in triage decisions.

Original languageEnglish (US)
Number of pages1
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
StatePublished - 2007

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