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Biomedical subjects

C Lovis

Publications and source records attributed to C Lovis.

51 records · Page 3Linked to original sources
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↗
PubMed1995

Toward a medical linguistic knowledge base.

This paper presents the design of a Medical Linguistic Knowledge Base (MLKB). This MLKB is intended to be the multilingual recipient for all the declarative knowledge about languages. It includes words, their syntax and their conceptual representation, typology of concepts of the domain, rules for semantic analysis and conceptual schemata. For that purpose, Sowa's conceptual graphs are considered as an adequate knowledge representation. The MLKB will be an enormous body of information, and the difficulty to feed it and to validate it appears immediately. Therefore, it is necessary to start an international initiative to merge efforts from different groups.

Language↗
PubMed1995

Word segmentation processing: a way to exponentially extend medical dictionaries.

One of the most critical problems of automatic natural language processing (NLP) is the size of the medical lexicons. The set of compound medical words and the continual creation of new terms renders medical lexicons exhaustive beyond question. The structure of such dictionaries usually consists of two parts: 1) the morphological and sometimes syntactical information necessary to identify, on a grapheme level, a given word in a sentence, and 2) the part often devoted to conceptual knowledge associated with the recognized word. It is only when these two prerequisites are fulfilled that an attempt to understand the meaning of a whole expression is possible. The approach developed in this paper is a pragmatic way to rapidly increase the lexico-semantic part of medical dictionaries. We developed a semi-automatic tool, as a prototype to demonstrate the feasibility of this approach. This tool is able to translate almost any diagnosis expressed in French into its equivalent in the ICD-9CM coding scheme.

Dictionaries, Medical as Topic↗
PubMed1995

Constructing clinical applications: the GALEN approach.

A common problem for developers of clinical applications is coping with the diversity of medical language. Medical language as it is used all over the world varies widely, while the referents for these words stay essentially the same. Software developers must reconcile this diversity with the practical necessity of producing applications that are usable in a variety of hospitals, while ensuring that information can be shared between applications. Existing approaches center around coding and classification schemes, but these approaches must be supplemented by a range of sophisticated terminological services in order for the language barriers to be overcome. To address this, the GALEN project is developing an application called the Terminology Server to provide such a range of terminological services (e.g., conceptual and multilingual services). The software is built upon a re-usable core model of medical terminology. This paper reports on the development of a clinical application called the SCUI (Structured Clinical User Interface) which draws on these GALEN technologies and illustrates an innovative approach to the construction of future clinical applications. The SCUI was specifically developed and tested in the context of infectious diseases to satisfy the demands made by the medical intensive care unit on the Geneva Hospital's microbiology laboratory.

Clinical Laboratory Information Systems↗
PubMed1995

LUCID: a semi-automated ICD-9 encoding system.

The natural language approach to diagnosis encoding will certainly become a widespread technique during the second half of this decade. Accessing standard codes by numbers and keywords will be more and more considered a loss of time and efficiency. We present a demonstration of a natural language based encoding system for ICD, called LUCID, which considerably alleviates the burden of coding with ICD classification and enhances the quality of the encoded list of diagnoses. This tool, delivered on a PC platform, is very convivial and provides a versatile interface to any existing application based on Microsoft Windows standards.

Abstracting and Indexing↗
PubMed1995

Hospital network: a low cost PC-based solution.

A new shell has been developed for Windows 3.1 that allows the use of low-cost PCs and their local processing power within a large hospital network, while conserving a good security and maintenance level.

Computer Security↗
PubMed1995

Representing clinical narratives using conceptual graphs.

The analysis of medical narratives and the generation of natural language expressions are strongly dependent on the existence of an adequate representation language. Such a language has to be expressive enough in order to handle the complexity of human reasoning in the domain. Sowa's Conceptual Graphs (CG) are an answer, and this paper presents a multilingual implementation, using French, English and German. Current developments demonstrate the feasibility of an approach to natural Language Understanding where semantic aspects are dominant, in contrast to syntax driven methods. The basic idea is to aggregate blocks of words according to semantic compatibility rules, following a method called Proximity Processing. The CG representation is gradually built, starting from single words in a semantic lexicon, to finally give a complete representation of the sentence under the form of a single CG. The process is dependent on specific rules of the medical domain, and for this reason is largely controlled by the declarative knowledge of the medical Linguistic Knowledge Base.

Artificial Intelligence↗
PubMed1994

Heat shock proteins and the kidney.

The heat shock (HS) response is remarkably conserved during evolution and is evoked under many conditions of stress. There are a number of ways in which this ubiquitous response may be important for the understanding of renal pathophysiology. Ischemia, toxin exposure, and oxidative stress induce this response. Several models of hypertension are associated with increased susceptibility to environmental stress and increased accumulation of heat shock protein mRNA. HSP70 polymorphism has been demonstrated when comparing normotensive and hypertensive rats. Heat shock proteins may play a role in renal diseases through their important involvement in immunological processes. Several observations point to a role of the heat shock response in systemic lupus erythematosus (SLE). Autoantibodies against HSP70 and ubiquitin are found in many patients with this disease. Autoantibodies against ubiquitin and ubiquitinated histone H2A are localized to the kidney glomerular basement membrane of SLE patients with active disease. A better understanding of the HS response may thus provide important insight into renal pathophysiology and may suggest paradigms for therapeutic interventions.

Adult↗
PubMed1994

Medical office automation integrated into the distributed architecture of a hospital information system.

Patient histories, discharge summaries, and medical consultant reports are made up of written texts. Therefore, the gathering and archiving of these texts in machine-readable form has many characteristics of computer-based medical records. In Geneva, approximately 1,540 PCs are connected to the Hospital Information System DIOGENE 2, with the possibility of accessing all the functions offered by the system without losing any of their MS-DOS word processing capabilities. The UNIDOC system, presented in this paper, takes all these features into account, a real marriage of technologies between the MS-DOS environment and the distributed client-server architecture. The INGRES database management system supports the entire archiving process of the medical patient texts, structured by prelabelled paragraphs and automatically indexed. Both the quality and accessibility of the records are enhanced, while the archiving capacity is neither too limited nor too expensive.

Archives↗
PubMed1993

Modelling for natural language understanding.

Natural Language Understanding (NLU) is a rapidly growing field in medical informatics. Its potential for tomorrow's applications is important. However, it is limited by its ability to ground its components on a solid model of the domain. This opens the way for the emergence of the discipline of medical domain modelling, as part of the vast field of Knowledge Base (KB) engineering. This article aims at describing the current development of a multilingual natural language system, strongly oriented towards the semantics of the domain. Special emphasis is presently given to the task of building a domain model, and to establish direct links with the language platform. The result is a model-driven NLU system. Numerous benefits are expected in the long term.

Artificial Intelligence↗
PubMedDate not supplied

Medical dictionaries for patient encoding systems: a methodology.

Medical language is highly compositional and makes extensive use of common roots, especially Latino-Greek roots. Besides words devoted to common sense, medical language presents some typical characteristics, especially on morphological and semantic aspects of word formation. Morphological decomposition and identification precedes semantic analysis. It is only when these two prerequisites are fulfilled that an attempt to grasp the meaning of a whole expression is made possible. The main aim of the proposed approach is that of coping with 'the lack of coverage of the medical lexical knowledge', in order to help physicians find the correct international classification for diseases (ICD) codes for a written diagnosis. The proposed methodology allows the development of a powerful dynamic dictionary dedicated to natural language processing in the field of diagnoses and narrative procedures. It describes the design of an analyser that can profit from a dictionary. The methods used have proved to be efficient for various classifications, s well as for multiple languages, as the system presently supports French, German, English and Dutch for ICD-9 and ICD-10 classifications.

Classification↗
PubMedDate not supplied

Trends and pitfalls with nomenclatures and classifications in medicine.

This paper reflects some of the main points in the history and the trends of classifications, nomenclatures and knowledge representation models in medicine. The relations with philosophical background are briefly related. The contributions in this field during the Medical Informatics Europe (MIE) conference in 1997 are presented. International collaborations in the field of lexico-semantic resources and inter-disciplinary partnership in natural language processing technologies are necessary steps to achieve definitive results that will lead to applications in the daily medical practice.

Algorithms↗
PubMedDate not supplied

Fast exact string pattern-matching algorithms adapted to the characteristics of the medical language.

OBJECTIVE: The authors consider the problem of exact string pattern matching using algorithms that do not require any preprocessing. To choose the most appropriate algorithm, distinctive features of the medical language must be taken into account. The characteristics of medical language are emphasized in this regard, the best algorithm of those reviewed is proposed, and detailed evaluations of time complexity for processing medical texts are provided. DESIGN: The authors first illustrate and discuss the techniques of various string pattern-matching algorithms. Next, the source code and the behavior of representative exact string pattern-matching algorithms are presented in a comprehensive manner to promote their implementation. Detailed explanations of the use of various techniques to improve performance are given. MEASUREMENTS: Real-time measures of time complexity with English medical texts are presented. They lead to results distinct from those found in the computer science literature, which are typically computed with normally distributed texts. RESULTS: The Boyer-Moore-Horspool algorithm achieves the best overall results when used with medical texts. This algorithm usually performs at least twice as fast as the other algorithms tested. CONCLUSION: The time performance of exact string pattern matching can be greatly improved if an efficient algorithm is used. Considering the growing amount of text handled in the electronic patient record, it is worth implementing this efficient algorithm.

Algorithms↗
PubMedDate not supplied

Evaluation of a command-line parser-based order entry pathway for the Department of Veterans Affairs electronic patient record.

OBJECTIVE: To improve and simplify electronic order entry in an existing electronic patient record, the authors developed an alternative system for entering orders, which is based on a command- interface using robust and simple natural-language techniques. DESIGN: The authors conducted a randomized evaluation of the new entry pathway, measuring time to complete a standard set of orders, and users' satisfaction measured by questionnaire. A group of 16 physician volunteers from the staff of the Department of Veterans Affairs Puget Sound Health Care System-Seattle Division participated in the evaluation. RESULTS: Thirteen of the 16 physicians (81%) were able to enter medical orders more quickly using the natural-language-based entry system than the standard graphical user interface that uses menus and dialogs (mean time spared, 16.06 +/- 4.52 minutes; P=0.029). Compared with the graphical user interface, the command--based pathway was perceived as easier to learn (P<0.01), was considered easier to use and faster (P<0.01), and was rated better overall (P<0.05). CONCLUSION: Physicians found the command- interface easier to learn and faster to use than the usual menu-driven system. The major advantage of the system is that it combines an intuitive graphical user interface with the power and speed of a natural-language analyzer.

Consumer Behavior↗