<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This paper presents an approach for Information Extraction (IE) from Patient Records (PRs) in Bulgarian. The specific terminology and lack of resources in electronic format are some of the obstacles that make the task of current patient status data extraction in a structured format quite challenging. The usage of N-grams, collocations and words’ distances allows us to cope with this problem and to extract automatically the attribute-value pairs with relatively high precision.</p></abstract>

This paper presents an approach for Information Extraction (IE) from Patient Records (PRs) in Bulgarian. The specific terminology and lack of resources in electronic format are some of the obstacles that make the task of current patient status data extraction in a structured format quite challenging. The usage of N-grams, collocations and words’ distances allows us to cope with this problem and to extract automatically the attribute-value pairs with relatively high precision.

Structured Information Extraction from Medical Texts in Bulgarian

American University in Bulgaria, 1 Georgi Izmirliev Sq., Blagoevgrad 2700

Cybernetics and Information Technologies

{"article-title":"Structured Information Extraction from Medical Texts in Bulgarian"}

This paper presents an approach for Information Extraction (IE) from Patient Records (PRs) in Bulgarian. The specific terminology and lack of resources in...

Structured Information Extraction from Medical Texts in Bulgarian

Online veröffentlicht: 22. März 2013

Seitenbereich: 52 - 65

DOI: https://doi.org/10.2478/cait-2012-0030

Schlüsselwörter
Artificial Intelligence, linguistic modeling, health informatics

This content is open access.

Structured Information Extraction from Medical Texts in Bulgarian

Online veröffentlicht: 22. März 2013

Seitenbereich: 52 - 65

DOI: https://doi.org/10.2478/cait-2012-0030

SchlüsselwörterArtificial Intelligence, linguistic modeling, health informatics

This content is open access.

Schlüsselwörter
Artificial Intelligence, linguistic modeling, health informatics