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Biomedical subjects

Marcelo Fiszman

Publications and source records attributed to Marcelo Fiszman.

7 recordsLinked to original sources
PubMed2005

Medical facts to support inferencing in natural language processing.

We report on the use of medical facts to support the enhancement of natural language processing of biomedical text. Inferencing in semantic interpretation depends on a fact repository as well as an ontology. We used statistical methods to construct a repository of drug-disorder co-occurrences from a large collection of clinical notes, and this resource is used to validate inferences automatically drawn during semantic interpretation of Medline citations about pharmacologic interventions for disease. We evaluated the results against a published reference standard for treatment of diseases.

Disease↗
PubMed2004

Identifying respiratory findings in emergency department reports for biosurveillance using MetaMap.

Clinical conditions described in patients' dictated reports are necessary for automated detection of patients with respiratory illnesses such as inhalational anthrax and pneumonia. We applied MetaMap to emergency department reports to extract a set of 71 clinical conditions relevant to detection of a lower respiratory outbreak. We indexed UMLS terms in emergency department reports with MetaMap, filtered the indexed output with a specialized lexicon of UMLS terms for the domain, and mapped the clinical conditions of interest to concepts in the lexicon. We compared MetaMap's ability to accurately identify the conditions against a physician's manual annotations and evaluated incorrectly indexed features to determine what additional processing is necessary. MetaMap identified the clinical conditions with a recall of 0.72 and a precision of 0.56. Necessary processing beyond MetaMap's indexing includes finding validation, temporal discrimination, anatomic location discrimination, finding-disease discrimination, and contextual inference. Successful identification of clinical conditions in an emergency department report with MetaMap requires processing techniques specific to the clinical question of interest.

Abstracting and Indexing↗
PubMed2004

Summarization of an online medical encyclopedia.

We explore a knowledge-rich (abstraction) approach to summarization and apply it to multiple documents from an online medical encyclopedia. A semantic processor functions as the source interpreter and produces a list of predications. A transformation stage then generalizes and condenses this list, ultimately generating a conceptual condensate for a given disorder topic. We provide a preliminary evaluation of the quality of the condensates produced for a sample of four disorders. The overall precision of the disorder conceptual condensates was 87%, and the compression ratio from the base list of predications to the final condensate was 98%. The conceptual condensate could be used as input to a text generator to produce a natural language summary for a given disorder topic.

Disease↗
PubMed2003

The interaction of domain knowledge and linguistic structure in natural language processing: interpreting hypernymic propositions in biomedical text.

Interpretation of semantic propositions in free-text documents such as MEDLINE citations would provide valuable support for biomedical applications, and several approaches to semantic interpretation are being pursued in the biomedical informatics community. In this paper, we describe a methodology for interpreting linguistic structures that encode hypernymic propositions, in which a more specific concept is in a taxonomic relationship with a more general concept. In order to effectively process these constructions, we exploit underspecified syntactic analysis and structured domain knowledge from the Unified Medical Language System (UMLS). After introducing the syntactic processing on which our system depends, we focus on the UMLS knowledge that supports interpretation of hypernymic propositions. We first use semantic groups from the Semantic Network to ensure that the two concepts involved are compatible; hierarchical information in the Metathesaurus then determines which concept is more general and which more specific. A preliminary evaluation of a sample based on the semantic group Chemicals and Drugs provides 83% precision. An error analysis was conducted and potential solutions to the problems encountered are presented. The research discussed here serves as a paradigm for investigating the interaction between domain knowledge and linguistic structure in natural language processing, and could also make a contribution to research on automatic processing of discourse structure. Additional implications of the system we present include its integration in advanced semantic interpretation processors for biomedical text and its use for information extraction in specific domains. The approach has the potential to support a range of applications, including information retrieval and ontology engineering.

Abstracting and Indexing↗
PubMed2003

Integrating a hypernymic proposition interpreter into a semantic processor for biomedical texts.

Semantic processing provides the potential for producing high quality results in natural language processing (NLP) applications in the biomedical domain. In this paper, we address a specific semantic phenomenon, the hypernymic proposition, and concentrate on integrating the interpretation of such predications into a more general semantic processor in order to improve overall accuracy. A preliminary evaluation assesses the contribution of hypernymic propositions in providing more specific semantic predications and thus improving effectiveness in retrieving treatment propositions in MEDLINE abstracts. Finally, we discuss the generalization of this methodology to additional semantic propositions as well as other types of biomedical texts.

Abstracting and Indexing↗
PubMed2003

Interpreting hypernymic propositions in an online medical encyclopedia.

Interpretation of semantic propositions from bio-medical texts documents would provide valuable support to natural language processing (NLP) applications. We are developing a methodology to interpret a kind of semantic proposition, the hypernymic proposition, in MEDLINE abstracts. In this paper, we expanded the system to identify these structures in a different discourse domain: the Medical Encyclopedia from the National Library of Medi-cine's MEDLINEplus Website.

Encyclopedias as Topic↗