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Biomedical subjects

A R Aronson

Publications and source records attributed to A R Aronson.

At least 19 recordsLinked to original sources
PubMed2004

Application of a Medical Text Indexer to an online dermatology atlas.

Clinical dermatology cases are presented as images and semi-structured text describing skin lesions and their relationships to disease. Metadata assignment to such cases is hampered by lack of a standardized dermatology vocabulary and facilitated methods for indexing legacy collections. In this pilot study descriptive clinical text from Dermatlas, a Web-based repository of dermatology cases, was indexed to Medical Subject Heading (MeSH) terms using the National Library of Medicine's Medical Text Indexer (MTI). The MTI is an automated text processing system that derives ranked lists of MeSH terms to describe the content of medical journal citations using knowledge from the Unified Medical Language System (UMLS) and from MEDLINE. For a representative, random sample of 50 Dermatlas cases, the MTI frequently derived MeSH indexing terms that matched expert-assigned terms for Diagnoses (88%), Lesion Types (72%), and Patient Characteristics (Gender and Age Groups, 62% and 84% respectively). This pilot demonstrates the potential for extending the MTI to automate indexing of clinical case presentations and for using MeSH to describe aspects of clinical dermatology.

Abstracting and Indexing↗
PubMed2001

Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program.

The UMLS Metathesaurus, the largest thesaurus in the biomedical domain, provides a representation of biomedical knowledge consisting of concepts classified by semantic type and both hierarchical and non-hierarchical relationships among the concepts. This knowledge has proved useful for many applications including decision support systems, management of patient records, information retrieval (IR) and data mining. Gaining effective access to the knowledge is critical to the success of these applications. This paper describes MetaMap, a program developed at the National Library of Medicine (NLM) to map biomedical text to the Metathesaurus or, equivalently, to discover Metathesaurus concepts referred to in text. MetaMap uses a knowledge intensive approach based on symbolic, natural language processing (NLP) and computational linguistic techniques. Besides being applied for both IR and data mining applications, MetaMap is one of the foundations of NLM's Indexing Initiative System which is being applied to both semi-automatic and fully automatic indexing of the biomedical literature at the library.

Abstracting and Indexing↗
PubMed2001

Automatic MeSH term assignment and quality assessment.

For computational purposes documents or other objects are most often represented by a collection of individual attributes that may be strings or numbers. Such attributes are often called features and success in solving a given problem can depend critically on the nature of the features selected to represent documents. Feature selection has received considerable attention in the machine learning literature. In the area of document retrieval we refer to feature selection as indexing. Indexing has not traditionally been evaluated by the same methods used in machine learning feature selection. Here we show how indexing quality may be evaluated in a machine learning setting and apply this methodology to results of the Indexing Initiative at the National Library of Medicine.

Abstracting and Indexing↗
PubMed2001

Developing a test collection for biomedical word sense disambiguation.

Ambiguity, the phenomenon that a word has more than one sense, poses difficulties for many current Natural Language Processing (NLP) systems. Algorithms that assist in the resolution of these ambiguities, i.e. which make unambiguous a word, or more generally, a text string, will boost performance of these systems. To test such techniques in the biomedical language domain, we have developed a Word Sense Disambiguation (WSD) test collection that comprises 5,000 unambiguous instances for 50 ambiguous UMLS Metathesaurus strings.

Abstracting and Indexing↗
PubMed2000

The NLM Indexing Initiative.

The objective of NLM's Indexing Initiative (IND) is to investigate methods whereby automated indexing methods partially or completely substitute for current indexing practices. The project will be considered a success if methods can be designed and implemented that result in retrieval performance that is equal to or better than the retrieval performance of systems based principally on humanly assigned index terms. We describe the current state of the project and discuss our plans for the future.

Abstracting and Indexing↗
PubMed2000

Text-based discovery in biomedicine: the architecture of the DAD-system.

Current scientific research takes place in highly specialized contexts with poor communication between disciplines as a likely consequence. Knowledge from one discipline may be useful for the other without researchers knowing it. As scientific publications are a condensation of this knowledge, literature-based discovery tools may help the individual scientist to explore new useful domains. We report on the development of the DAD-system, a concept-based Natural Language Processing system for PubMed citations that provides the biomedical researcher such a tool. We describe the general architecture and illustrate its operation by a simulation of a well-known text-based discovery: The favorable effects of fish oil on patients suffering from Raynaud's disease [1].

Drug-Related Side Effects and Adverse Reactions↗
PubMed1999

Mining molecular binding terminology from biomedical text.

Automatic access to information regarding macromolecular binding relationships would provide a valuable resource to the biomedical community. We report on a pilot project to mine such information from the molecular biology literature. The program being developed takes advantage of natural language processing techniques and is supported by two repositories of biomolecular knowledge. A formative evaluation has been conducted on a subset of MEDLINE abstracts.

Algorithms↗
PubMed1999

Analysis of biomedical text for chemical names: a comparison of three methods.

At the National Library of Medicine (NLM), a variety of biomedical vocabularies are found in data pertinent to its mission. In addition to standard medical terminology, there are specialized vocabularies including that of chemical nomenclature. Normal language tools including the lexically based ones used by the Unified Medical Language System (UMLS) to manipulate and normalize text do not work well on chemical nomenclature. In order to improve NLM's capabilities in chemical text processing, two approaches to the problem of recognizing chemical nomenclature were explored. The first approach was a lexical one and consisted of analyzing text for the presence of a fixed set of chemical segments. The approach was extended with general chemical patterns and also with terms from NLM's indexing vocabulary, MeSH, and the NLM SPECIALIST lexicon. The second approach applied Bayesian classification to n-grams of text via two different methods. The single lexical method and two statistical methods were tested against data from the 1999 UMLS Metathesaurus. One of the statistical methods had an overall classification accuracy of 97%.

Algorithms↗
PubMed1997

Query expansion using the UMLS Metathesaurus.

Recent work has demonstrated the importance of query expansion for improving retrieval effectiveness when applying statistically-based systems to MEDLINE citations. The research has suggested the use of retrieval feedback for enhancing the original text of users' queries. As an alternative method of query expansion, we propose the use of the MetaMap program for associating UMLS Metathesaurus concepts with the original query. Our experiments show that query expansion based on MetaMap compares favorably with retrieval feedback. We conclude that the optimal strategy would be to combine the two techniques.

Abstracting and Indexing↗
PubMed1996

Finding the findings: identification of findings in medical literature using restricted natural language processing.

The ability to search the biomedical literature based on findings would provide enhanced access to information. We describe a computer program called FINDX which relies on the UMLS Metathesuaurus and restricted natural language processing to identify findings in free text. Such identification can serve as a filtering mechanism while selecting relevant papers. After discussing the salient characteristics of findings on which FINDX depends, we report on the results of an experiment in which we tested the program on a set of MEDLINE abstracts pertaining to the diagnosis of Parkinson Disease.

Humans↗
PubMed1996

The effect of textual variation on concept based information retrieval.

Accounting for textual variation in the documents and queries processed by information retrieval systems is considered essential for achieving good retrieval. Recent research has called into question several of the techniques used to support this endeavor. This paper reports on experiments with a concept based information retrieval system which relies on a program called MetaMap to account for textual variation in the process of mapping biomedical text such as MEDLINE bibliographic citations to the UMLS Metathesaurus. The experiments confirm that the effort expended in handling textual variation is well-spent for at least one type of concept based information retrieval.

Information Storage and Retrieval↗
PubMed1994

Ambiguity resolution while mapping free text to the UMLS Metathesaurus.

We propose a method for resolving ambiguities encountered when mapping free text to the UMLS Metathesaurus. Much of the research in medical informatics involves the manipulation of free text. The Metathesaurus contains extensive information which supports solutions to problems encountered while processing such text. After discussing the process of mapping free text to the Metathesaurus and describing the ambiguities which are often the result of such mapping, we provide examples of rules designed to eliminate mapping ambiguities. These rules refer to the context in which the ambiguity occurs and crucially depend on semantic types obtained from the Metathesaurus. We have conducted a preliminary test of the methodology and the results obtained indicate that the rules successfully resolve ambiguity around 80% of the time.

Abstracting and Indexing↗
PubMed1993

Semantic processing in information retrieval.

Intuition suggests that one way to enhance the information retrieval process would be the use of phrases to characterize the contents of text. A number of researchers, however, have noted that phrases alone do not improve retrieval effectiveness. In this paper we briefly review the use of phrases in information retrieval and then suggest extensions to this paradigm using semantic information. We claim that semantic processing, which can be viewed as expressing relations between the concepts represented by phrases, will in fact enhance retrieval effectiveness. The availability of the UMLS domain model, which we exploit extensively, significantly contributes to the feasibility of this processing.

Information Storage and Retrieval↗
PubMed1993

UMLS knowledge for biomedical language processing.

This paper describes efforts to provide access to the free text in biomedical databases. The focus of the effort is the development of SPECIALIST, an experimental natural language processing system for the biomedical domain. The system includes a broad coverage parser supported by a large lexicon, modules that provide access to the extensive Unified Medical Language System (UMLS) Knowledge Sources, and a retrieval module that permits experiments in information retrieval. The UMLS Metathesaurus and Semantic Network provide a rich source of biomedical concepts and their interrelationships. Investigations have been conducted to determine the type of information required to effect a map between the language of queries and the language of relevant documents. Mappings are never straightforward and often involve multiple inferences.

Humans↗
PubMed1977

Controlled trials of aluminum hydroxide gels for peptic ulcer.

Relief of duodenal ulcer pain by aluminum hydroxide gel (AG) was compared with that obtained by a dummy gel (DG) in randomized trials. In 44 individual pain episodes, complete relief was obtained by 15-ml doses of AG in 79% and by DG in 45% (P less than 0.05). In 48 identical blind trials replicated at another hospital the difference was not significant. The gels were also tested against ulcer pain induced by intragastric acid instillation (Palmer test) in 35 patients; pain was relieved by AG in 63% and by DG in 62%. Presumed effectiveness in terminating ulcer episodes was studied in 65 patients admitted for pain; 37 received milk and cream hourly and 28 did not. All were treated with 15 ml of AG or DG during waking hours. Median time for complete disappearance of spontaneous pain was 3 days for AG and 7 days for DG, the same in both groups. In all patients the acid instillation test was repeated every few days. For the milk and cream group it became negative after 4 days with AG and after 6 days with DG. In 18 patients with gastric ulcer treated for 4 weeks AG led to greater reductions in size than did DG. A number of these trials indicate AG to be more effective than DG, but sampling and other methodological problems limit the certainty of any conclusions.

Aluminum Hydroxide↗