Name
Abstract | ||
|---|---|---|
ICD-coding is a complex and difficult task. Coding results vary a great deal depending on each coder's ability. Although the Japanese Standard Disease-Code Master facilitates the coding tasks, it also engenders post-coordination problems derived from combinations of basic diseases (with ICD code) and modifiers. Post-coordination sometimes alters the original ICD code dramatically. To solve this problem, this paper presents a proposal for using internal structures of disease names to correct the ICD code. First, we built an internal structure analyzer, which achieved high (83.7%) accuracy. Results demonstrated that the analyzed output is helpful for precise ICD-coding tasks. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.3233/978-1-60750-588-4-1010 | Studies in Health Technology and Informatics |
Keywords | Field | DocType |
ICD-10,Disease name,Multi-word expression,Internal structure,Dependency analysis,Post-coordination | Data mining,Disease,Computer science,Coding (social sciences) | Conference |
Volume | Issue | ISSN |
160 | Pt 2 | 0926-9630 |
Citations | PageRank | References |
1 | 0.35 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Emiko Yamada | 1 | 1 | 0.35 |
| Eiji Aramaki | 2 | 1 | 0.35 |
| Takeshi Imai | 3 | 1 | 1.37 |
| Kazuhiko Ohe | 4 | 115 | 15.91 |