Biomedical subjects

N T Nhàn

Publications and source records attributed to N T Nhàn.

6 recordsLinked to original sources

PubMed1998

Medical language processing applied to extract clinical information from Dutch medical documents.

In this paper, we want to show how an existing morpho-syntactic analyser for Dutch (Dutch Medical Language Processor--DMLP) has been extended in order to produce output that is compatible with the language independent modules of the LSP-MLP system (Linguistic String Project--Medical Language Processor) of the New York University. The former can focus on idiosyncrasies for Dutch and take advantage of the language independent developments of the latter. This general strategy will be illustrated by a practical application, namely the extraction of clinical information from Dutch patient discharge summaries. Such an application can be of use for education, research and quality control purposes in a hospital environment.

Humans↗

PubMed1996

Medical language processing with SGML display.

The paper demonstrates several ways that medical language processing can be combined with emerging display technologies to facilitate the extraction of data from free-text patient documents. The techniques allow rapid review via highlighting of the results of processing. Coupling of text markup with further procedures is envisioned.

Asthma↗

PubMed1995

Medical language processing: applications to patient data representation and automatic encoding.

A linguistic approach is presented to develop a representation of patient data. Semantic categories developed for computer processing of narrative clinical reports are shown to be similar to the Medical Concepts used manually to extract data from narrative in Exercises of the Computer-based Patient Record Institute. Clinical statement types composed of these categories are used in the Linguistic String Project (LSP) medical language processing (MLP) system to convert narrative information into relational database tables of patient information. A procedure for mapping the output of the LSP MLP system into SNOMED International codes was developed. Preliminary results and further requirements are discussed.

Abstracting and Indexing↗

PubMed1994

Automatic encoding into SNOMED III: a preliminary investigation.

The Linguistic String Project (LSP) medical language processing (MLP) system converts narrative clinical reports into database tables of patient data. A procedure for mapping the output of the LSP MLP system into SNOMED III codes was developed. Preliminary results and further requirements are discussed.

Abstracting and Indexing↗

PubMed1993

Natural language processing of asthma discharge summaries for the monitoring of patient care.

A technique for monitoring healthcare via the processing of routinely collected narrative documentation is presented. A checklist of important details of asthma management in use in the Glasgow Royal Infirmary (GRI) was translated into SQL queries and applied to a database of 59 GRI discharge summaries analyzed by the New York University Linguistic String Project medical language processor. Tables of retrieved information obtained for each query were compared with the text of the original documents by physician reviewers. Categories (unit = document) were: (1) information present, retrieved correctly; (2) information not present; (3) information present, retrieved with minor or major error; (4) information present, retrieved with minor or major omissions. Category 2 (physician "documentation score") could be used to prioritize manual review and guide feedback to physicians to improve documentation. The semantic structuring and relative completeness of retrieved data suggest their potential use as input to further quality assurance procedures.

Asthma↗

PubMed1991

TEXTINFO: a tool for automatic determination of patient clinical profiles using text analysis.

The clinical data contained in narrative patient documents is made available via grammatical and semantic processing. Retrievals from the resulting relational database tables are matched against a set of clinical descriptors to obtain clinical profiles of the patients in terms of the descriptors present in the documents. Discharge summaries of 57 Dept. of Digestive Surgery patients were processed in this manner. Factor analysis and discriminant analysis procedures were then applied, showing the profiles to be useful for diagnosis definitions (by establishing relations between diagnoses and clinical findings), for diagnosis assessment (by viewing the match between a definition and observed events recorded in a patient text), and potentially for outcome evaluation based on the classification abilities of clinical signs.

Databases, Factual↗