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PubMed2001

Using narrative reports to support a digital library.

The vast amount of information collected and stored in clinical systems can be a significant challenge in the integration of digital libraries and electronic medical records, especially the selection of clinical data to be used in the search, retrieval, and summarization processes. In this study, we describe the use of information retrieval measures with natural language processor output to identify critical information in narrative reports. Our hypothesis is that clinical data that occur often in narrative reports are less important to clinicians than findings that occur rarely. We used the information retrieval methods to analyze one year of discharge summaries. We then conducted a performance study, using physicians as subject. Results show that the methods can be used for filtering critical information from reports. Further studies need to be done on evaluation of the method based on an evaluation of the system performance in the context of a digital library.

Humans↗
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↗
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↗
PubMed2006

Development and validation of queries using structured query language (SQL) to determine the utilization of comparison imaging in radiology reports stored on PACS.

The purpose of this research was to develop queries that quantify the utilization of comparison imaging in free-text radiology reports. The queries searched for common phrases that indicate whether comparison imaging was utilized, not available, or not mentioned. The queries were iteratively refined and tested on random samples of 100 reports with human review as a reference standard until the precision and recall of the queries did not improve significantly between iterations. Then, query accuracy was assessed on a new random sample of 200 reports. Overall accuracy of the queries was 95.6%. The queries were then applied to a database of 1.8 million reports. Comparisons were made to prior images in 38.69% of the reports (693,955/1,793,754), were unavailable in 18.79% (337,028/1,793,754), and were not mentioned in 42.52% (762,771/1,793,754). The results show that queries of text reports can achieve greater than 95% accuracy in determining the utilization of prior images.

Database Management Systems↗
PubMed1996

The expert surgical assistant. An intelligent virtual environment with multimodal input.

Virtual Reality has made computer interfaces more intuitive but not more intelligent. This paper shows how an expert system can be coupled with multimodal input in a virtual environment to provide an intelligent simulation tool or surgical assistant. This is accomplished in three steps. First, voice and gestural input is interpreted and represented in a common semantic form. Second, a rule-based expert system is used to infer context and user actions from this semantic representation. Finally, the inferred user actions are matched against steps in a surgical procedure to monitor the user's progress and provide automatic feedback. In addition, the system can respond immediately to multimodal commands for navigational assistance and/or identification of critical anatomical structures. To show how these methods are used we present a prototype sinus surgery interface. The approach described here may easily be extended to a wide variety of medical and non-medical training applications by making simple changes to the expert system database and virtual environment models. Successful implementation of an expert system in both simulated and real surgery has enormous potential for the surgeon both in training and clinical practice.

Artificial Intelligence↗
PubMed2000

The automation of coding.

Automated coding is a rapidly growing technology. The implications of this technology for the clinical, business, and research areas of health care today are dramatic. Before a health care organization chooses an automated coding system it is important that the implications of each of the various types as well as the vocabulary to be chosen are understood. This article will discuss three types of automated coding systems that are currently available, but it will not discuss the merits of the various vocabularies available for use in an automated coding system.

Abstracting and Indexing↗
PubMed1994

Automatic SNOMED coding.

Medical coding has become an important new industry that has originated from the field of medical informatics. Automatic coding of specimens has emerged as a way of relieving hospitals from the cost of paying professional coders and for achieving uniform coding for all specimens. Unfortunately, automatic coding, like manual coding, has numerous pitfalls. Further, the coding algorithms employed by manufacturers of automatic coders are typically proprietary. We have developed a method for automatic coding of pathology reports. Using this public domain autocoder, we have previously demonstrated that automatic SNOMED coding was superior to manual coding in several measurable categories, including the overall number of codes generated and the number of distinct code entities provided. In this report, we describe an algorithm that executes this strategy in the M-Technology environment.

Algorithms↗
PubMedDate not supplied

Understanding clinical narrative text.

A linguistic analysis of the narrative which appears in patient documents, in the domain of urology, has shown that the information is conveyed by a small number of semantic statement types composed of syntactic combinations of medical and English word classes. It has been shown that words from different classes occurring in the diagnosis for the patient disease follow some regular grammatical rules. This impressive linguistic regularity in clinical narrative has made it encouraging to develop a recognizer which is capable of recognizing disease diagnosis in the narrative clinical documents in the domain of urology. The recognizer was implemented using the C language. This recognizer output information which could be refined to a form suitable for management by a database management system for further computerized information processing.

Algorithms↗
PubMed2002

Communication in science.

Science must have a common language. For centuries, Latin language carried out this job, but the progress in computer technology and internet world through the last 20 years, began to produce a new language with the new century; the computer language. The information masses, which need data language standardization, are the followings; Digital libraries and medical education systems, Consumer health informatics, Medical education systems, World Wide Web Applications, Database systems, Medical language processing, Automatic indexing systems, Image processing units, Telemedicine, New Generation Internet (NGI).

Communication↗
PubMed2005

Automatic processing of multilingual medical terminology: applications to thesaurus enrichment and cross-language information retrieval.

OBJECTIVES: We present in this article experiments on multi-language information extraction and access in the medical domain. For such applications, multilingual terminology plays a crucial role when working on specialized languages and specific domains. MATERIAL AND METHODS: We propose firstly a method for enriching multilingual thesauri which extracts new terms from parallel corpora, and secondly, a new approach for bilingual lexicon extraction from comparable corpora, which uses a bilingual thesaurus as a pivot. We illustrate their use in multi-language information retrieval (English/German) in the medical domains. RESULTS: Our experiments show that these automatically extracted bilingual lexicons are accurate enough (85% precision for term extraction) for semi-automatically enriching mono- or bi-lingual thesauri such as the universal medical language system, and that their use in cross-language information retrieval significantly improves the retrieval performance (from 22 to 40% average precision) and clearly outperforms existing bilingual lexicon resources (both general lexicons and specialized ones). CONCLUSION: We show in this paper first that bilingual lexicon extraction from parallel corpora in the medical domain could lead to accurate, specialized lexicons, which can be used to help enrich existing thesauri and second that bilingual lexicons extracted from comparable corpora outperform general bilingual resources for cross-language information retrieval.

Electronic Data Processing↗
PubMed2006

Automatic lexeme acquisition for a multilingual medical subword thesaurus.

PURPOSE: We present a method for the automated acquisition of a multilingual medical lexicon (for Spanish, French and Swedish) to be used within the framework of a medical cross-language text retrieval system. METHODS: For the lexical acquisition process, we incorporate seed lexicons and lists of trusted term translations derived from the UMLS Metathesaurus. The seed lexicons for Spanish, French and Swedish are automatically generated from (previously manually constructed) Portuguese, German and English sources by simple string transformations. Lexical and semantic hypotheses are then validated by processing pairs of term translations. In a last step, we use the cleaned list of "approved" translations in order to augment, step by step, the target dictionaries by processing the parallel corpora in terms of co-occurrence patterns of hypothesized translation equivalents which cannot be derived by simple character substitutions. RESULTS: An existing multilingual lexicon for the medical domain with about 60,000 entries for English, German, and Portuguese was automatically augmented by more then 17,000 new lexemes for Spanish, French, and Swedish. CONCLUSIONS: Our approach constitutes a promising method for the automated creation of new lexicon entries and their linkage to semantic identifiers.

Electronic Data Processing↗
PubMed1999

Brain potentials indicate immediate use of prosodic cues in natural speech processing.

Spoken language, in contrast to written text, provides prosodic information such as rhythm, pauses, accents, amplitude and pitch variations. However, little is known about when and how these features are used by the listener to interpret the speech signal. Here we use event-related brain potentials (ERP) to demonstrate that intonational phrasing guides the initial analysis of sentence structure. Our finding of a positive shift in the ERP at intonational phrase boundaries suggests a specific on-line brain response to prosodic processing. Additional ERP components indicate that a false prosodic boundary is sufficient to mislead the listener's sentence processor. Thus, the application of ERP measures is a promising approach for revealing the time course and neural basis of prosodic information processing.

Brain↗
PubMed1991

A free-text processing system to capture physical findings: Canonical Phrase Identification System (CAPIS).

The task of gathering detailed patient information from free-text medical records presents a significant barrier to clinical research. In this paper, we describe a prototype system for extracting physical examination findings from dictated admission summaries. Our computer program applies a concept-based free-text processing algorithm that identifies user-selected target physical examination findings. We are using the extraction system to enrich an existing clinical database. The system was evaluated by comparing the physical examination findings extracted by our computer program with findings extracted by an independent investigator. Our prototype system was able to recall 92 percent (sensitivity) of the relevant physical findings, with a precision of 96 percent (positive predictive value).

Algorithms↗
PubMed1993

Structuration and acquisition of medical knowledge. Using UMLS in the conceptual graph formalism.

The use of a taxonomy, such as the concept type lattice (CTL) of Conceptual Graphs, is a central structuring piece in a knowledge-based system. The knowledge it contains is constantly used by the system, and its structure provides a guide for the acquisition of other pieces of knowledge. We show how UMLS can be used as a knowledge resource to build a CTL and how the CTL can help the process of acquisition for other kinds of knowledge. We illustrate this method in the context of the MENELAS natural language understanding project.

Artificial Intelligence↗
PubMed1997

Compositional and enumerative designs for medical language representation.

Medical language is in essence highly compositional, allowing complex information to be expressed from more elementary pieces. Embedding the expressive power of medical language into formal systems of representation is recognized in the medical informatics community as a key step towards sharing such information among medical record, decision support, and information retrieval systems. Accordingly, such representation requires managing both the expressiveness of the formalism and its computational tractability, while coping with the level of detail expected by clinical applications. These desiderata can be supported by enumerative as well as compositional approaches, as argued in this paper. These principles have been applied in recasting a frame-based system for general medical findings developed during the 1980s. The new system captures the precise meaning of a subset of over 1500 medical terms for general internal medicine identified from the Quick Medical Reference (QMR) lexicon. In order to evaluate the adequacy of this formal structure in reflecting the deep meaning of the QMR findings, a validation process was implemented. It consists of automatically rebuilding the semantic representation of the QMR findings by analyzing them through the RECIT natural language analyzer, whose semantic components have been adjusted to this frame-based model for the understanding task.

Internal Medicine↗
PubMed1995

Analysis of medical texts based on a sound medical model.

Automatic understanding of natural language is a complex task due to the presence of ambiguities. In particular, semantic ambiguities which are often immediately and unconsciously solved by human beings, are raised when analyzing natural language sentences by computer. The latter has to know the implicit and contextual information in order to resolve these difficulties. Nowadays in medicine, a considerable effort is deployed to model semantic contents of the medical domain. Such a task is usually performed separately from linguistic considerations. The goal of this paper is to highlight the key issues of basing a medical language processing system on a sound semantic model. To illustrate the requirements and advantages of such a conceptual approach to the analysis process, the experiment conducted to adjust the RECIT analyzer to the GALEN model is shown.

Models, Theoretical↗