Accession Number:

ADA551980

Title:

Free-Text Disease Classification

Descriptive Note:

Master's thesis

Corporate Author:

NAVAL POSTGRADUATE SCHOOL MONTEREY CA

Personal Author(s):

• Maxey, Craig

Report Date:

2011-09-01

Pagination or Media Count:

107.0

Abstract:

Modern medicine produces data with every patient interaction. While many data elements are easily captured and analyzed, the fundamental record of the patientclinician interaction is captured in written, free-text. This thesis provides the foundation for the Military Health System to begin building an auto classifier for ICD9 diagnostic codes based on free-text clinician notes. Support Vector Machine models are fit to approximately 84,000 free-text records providing a means to predict ICD9 codes for other free-text records. While the research conducted in this thesis does not provide a consumate ICD9 classification model, it does provide the foundation required to further more detailed analysis.

Descriptors:

• *AUTOMATIC
• *CLASSIFICATION
• *RECORDS
• *TEXT PROCESSING
• AUTOMATION
• CLINICAL MEDICINE
• CODING
• DATA MINING
• DIAGNOSIS(MEDICINE)
• DISEASES
• THESES

Subject Categories:

• Information Science
• Medicine and Medical Research
• Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE