A system for automated lexical mapping
Name
62171901-MIT.pdf
Description
Full printable version
Size
1.53 MB
Format
Adobe PDF
Checksum (MD5)
e0c72c3db061051e2180fab92fceeac9
Author(s)
Sun, Jennifer Y. (Jennifer Yiling)
Advisor(s)
Isaac S. Kohane.
Date Issued
2005
Publisher
Massachusetts Institute of Technology
Abstract
Merging of clinical systems and medical databases, or aggregation of information from disparate databases, frequently requires a process where vocabularies are compared and similar concepts are mapped. Using a normalization phase followed by a novel alignment stage inspired by DNA sequence alignment methods, automated lexical mapping can map terms from various databases to standard vocabularies such as UMLS (Unified Medical Language System) and SNOMED (the Systematized Nomenclature of Medicine). This automated lexical mapping was evaluated using a real-world database of consultation letters from Children's Hospital Boston. The first phase involved extracting the reason for referral from the consultation letters. The reasons for referral were then mapped to SNOMED. The alignment algorithm was able to map 72% of equivalent concepts through lexical mapping alone. Lexical mapping can facilitate the integration of data from diverse sources and decrease the time and cost required for manual mapping and integration of clinical systems and medical databases.
Description
Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology, 2005.
Includes bibliographical references (leaves 19-20).
Subjects
Harvard University--MIT Division of Health Sciences and Technology.
MIT Department
Harvard University--MIT Division of Health Sciences and Technology
Terms of Use
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Persistent DSpace Link
