Name
Abstract | ||
|---|---|---|
An important amount of clinical data concerning the medical history of a patient is in the form of clinical reports that are written by doctors. They describe patients, their pathologies, their personal and medical histories, findings made during interviews or during procedures, and so forth. They represent a source of precious information that can be used in several applications such as research information to diagnose new patients, epidemiological studies, decision support, statistical analysis, and data mining. But this information is difficult to access, as it is often in unstructured text form. To make access to patient data easy, our research aims to develop a system for extracting information from unstructured text. In a previous work, a rule-based approach is applied to a clinical reports corpus of infectious diseases to extract structured data in the form of named entities and properties. In this paper, we propose the use of a Boolean inference engine, which is based on a cellular automaton, to do extraction. Our motivation to adopt this Boolean modeling approach is twofold: first optimize storage, and second reduce the response time of the entities extraction. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.3745/JIPS.2012.8.1.067 | JOURNAL OF INFORMATION PROCESSING SYSTEMS |
Keywords | Field | DocType |
Clinical Reports, Information Extraction, Cellular Automaton, Boolean Inference Engine | Cellular automaton,Information retrieval,Computer science,Decision support system,Computer network,Information extraction,Medical history,Inference engine,Artificial intelligence,Data model,Machine learning,Statistical analysis | Journal |
Volume | Issue | ISSN |
8 | 1 | 1976-913X |
Citations | PageRank | References |
1 | 0.35 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fatiha Barigou | 1 | 14 | 6.76 |
| Baghdad Atmani | 2 | 70 | 18.72 |
| Bouziane Beldjilali | 3 | 65 | 9.29 |