Name
Title | ||
|---|---|---|
Finding malignant findings from radiological reports using medical attributes and syntactic information. |
Abstract | ||
|---|---|---|
Radiology reports are written primarily in natural language. Automated extraction of malignant findings from narrative reports is an important technique for clinical support or alert generation for physicians. This paper proposes a method for automatically extracting malignant findings from narrative radiological reports written in Japanese. First, sentences are parsed and a medical attribute of each phrase is determined Next, sub-trees related to radiological findings are extracted from a dependency tree using medical attributes. Finally, the malignant findings in each sub free are extracted with their positive or negative assertions, each of which is determined by the multiplication of pos/neg signs along a path in a sub-tree. The recall and precision for the extraction of malignant findings with their positive or negative assertions were 76% and 91% respectively. The experimental results showed the validity of the proposed method for extracting malignant findings with correct assertions. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.3233/978-1-58603-774-1-540 | Studies in Health Technology and Informatics |
Keywords | Field | DocType |
information extraction,radiology report,radiological findings,syntactic analysis,natural language processing | Data mining,Dependency tree,Computer science,Phrase,Natural language processing,Artificial intelligence,Syntax,Information retrieval,Precision and recall,Narrative,Natural language,Parsing,Radiological weapon | Conference |
Volume | Issue | ISSN |
129 | Pt 1 | 0926-9630 |
Citations | PageRank | References |
2 | 0.46 | 1 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Takeshi Imai | 1 | 20 | 3.73 |
| Eiji Aramaki | 2 | 371 | 45.89 |
| Masayuki Kajino | 3 | 2 | 1.13 |
| Kengo Miyo | 4 | 24 | 5.65 |
| Yuzo Onogi | 5 | 2 | 2.15 |
| Kazuhiko Ohe | 6 | 115 | 15.91 |