Biomedical subjects

R H Baud

Publications and source records attributed to R H Baud.

15 recordsLinked to original sources

PubMed1998

Internet integrated in the daily medical practice within an electronic patient record.

Healthcare enters the information age and professionals are finding an ever-growing role for computers in the daily practice of medicine. However, a number of problematic issues are associated with electronic publications, especially through Internet. Whilst access to any information has been improved, access to specific information has become more and more difficult [1], due to the lack of a general meta-knowledge allowing to structure Internet resources. Physicians have to learn and adapt themselves to computers and Internet, but Internet has to meet the specific requirements of Healthcare. Important issues must therefore be addressed to allow a real and daily use of Internet in the medical practice. The paper discusses most of these issues and proposes a solution developed at the University Hospital of Geneva that integrates an Electronic Patient Record with Internet, without compromises on security or on performances and that runs on standard PCs'.

Computer Security↗

PubMed1998

Alternative ways for knowledge collection, indexing and robust language retrieval.

Definitions are provided of the key entities in knowledge representation for Natural Language Processing (NLP). Starting from the words, which are the natural components of any sentence, both the role of expressions and the decomposition of words into their parts are emphasized. This leads to the notion of concepts, which are either primitive or composite depending on the model where they are created. The problem of finding the most adequate degree of granularity for a concept is studied. From this reflection on basic Natural Language Processing components, four categories of linguistic knowledge are recognized, that are considered to be the building blocks of a Medical Linguistic Knowledge Base (MLKB). Following on the tracks of a recent experience in building a natural language-based patient encoding browser, a robust method for conceptual indexing and query of medical texts is presented with particular attention to the scheme of knowledge representation.

Abstracting and Indexing↗

PubMed1998

Modeling concepts in medicine for medical language understanding.

Over the past two decades, the construction of models for medical concept representation and for understanding of the deep meaning of medical narrative texts have been challenging areas of medical informatics research. This review highlights how these two inter-related domains have evolved, emphasizing aspects of medical modeling as a tool for medical language understanding. A representation schema, which balances partially but accurately with complete but complex representations of domain-specific knowledge, must be developed to facilitate language understanding. Representative examples are drawn from two major independent efforts undertaken by the authors: the elaboration and the subsequent adjustment of the RECIT multilingual analyzer to include a robust medical concept model, and the recasting of a frame-based interlingua system, originally developed to map equivalent concepts between controlled clinical vocabularies, to invoke a similar concept model.

Artificial Intelligence↗

PubMed1998

Versatility of a multilingual and bi-directional approach for medical language processing.

At the dawn of the 21st century, we are experiencing an exponential growth of online information that is mostly textual, and that benefits from new electronic media, such as the World Wide Web (WWW), to be broadly diffused across borders. However, there is a gap to bridge between holding information and accessing in a relevant way the deep underlying knowledge. Multilingual natural language processing (NLP), once tuned, is certainly the best solution to cope with this era of textual information. This paper focuses on the lesson learned through the joint development of an analyzer and a generator of medical language, within a multilingual context. Concrete examples, derived from the efforts under way in the European GALEN-IN-USE project, illustrate the use of these linguistic tools for the handling of surgical procedures.

Multilingualism↗

PubMed1998

Morpho-semantic parsing of medical expressions.

The task of editing, indexing, storing, and retrieving medical expressions within medical records remains the main objective for the years to come. Therefore, the need for a parser with semantic capabilities able to robustly extract an essential part of the knowledge embedded in the medical record is paramount. The minimal requirements before considering clinical trials are that such a system has to be in position to handle any source of medical information and to conveniently grasp the main key concepts with low silence, good recognition of modalities and acceptable noise. This paper shows that the potential of morpho-semantic parsing is high to meet these conditions. This technique is an important complement to the traditional lexical approach and to expression-oriented systems like controlled vocabularies.

Language↗

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↗

PubMed1996

Knowledge sources for Natural Language Processing.

This paper aims at reviewing the problem of feeding Natural Language Processing (NLP) tools with convenient linguistic knowledge in the medical domain. A syntactic approach lacks the potential to solve a number of typical situations with ambiguities and is clearly insufficient for quality treatment of natural language. On the other hand, a conceptual approach relies on some modelling of the domain, of which the elaboration is d long-term process and where the ultimate solutions are far from being recognised and universally accepted. In-between is the beauty of the compromise. How can we significantly improve the coverage of linguistic knowledge in the years to come?

Artificial Intelligence↗

PubMed1996

Modeling principles for QMR medical findings.

Structured representation of medical information is essential for ensuring the accuracy and reliability of computerized decision support applications. Such systems require input that is error-free and clinically pertinent. This paper reviews existing medical models, particularly those exploited for natural language understanding, and highlights modeling features important to future indexing of medical texts with controlled vocabularies. A hybrid representation derived from existing frame-based and conceptual-graph-based systems is proposed to represent relevant medical terms as used by experts.

Abstracting and Indexing↗

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

Multilingual natural language generation as part of a medical terminology server.

Re-usable and sharable, and therefore language-independent concept models are of increasing importance in the medical domain. The GALEN project (Generalized Architecture for Languages Encyclopedias and Nomenclatures in Medicine) aims at developing language-independent concept representation systems as the foundations for the next generation of multilingual coding systems. For use within clinical applications, the content of the model has to be mapped to natural language. A so-called Multilingual Information Module (MM) establishes the link between the language-independent concept model and different natural languages. This text generation software must be versatile enough to cope at the same time with different languages and with different parts of a compositional model. It has to meet, on the one hand, the properties of the language as used in the medical domain and, on the other hand, the specific characteristics of the underlying model and its representation formalism. We propose a semantic-oriented approach to natural language generation that is based on linguistic annotations to a concept model. This approach is realized as an integral part of a Terminology Server, built around the concept model and offering different terminological services for clinical applications.

Language↗

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

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↗

PubMed1992

Natural language processing and semantical representation of medical texts.

For medical records, the challenge for the present decade is Natural Language Processing (NLP) of texts, and the construction of an adequate Knowledge Representation. This article describes the components of an NLP system, which is currently being developed in the Geneva Hospital, and within the European Community's AIM programme. They are: a Natural Language Analyser, a Conceptual Graphs Builder, a Data Base Storage component, a Query Processor, a Natural Language Generator and, in addition, a Translator, a Diagnosis Encoding System and a Literature Indexing System. Taking advantage of a closed domain of knowledge, defined around a medical specialty, a method called proximity processing has been developed. In this situation no parser of the initial text is needed, and the system is based on semantical information of near words in sentences. The benefits are: easy implementation, portability between languages, robustness towards badly-formed sentences, and a sound representation using conceptual graphs.

Abstracting and Indexing↗

PubMedDate not supplied

Natural language generation of surgical procedures.

A number of compositional Medical Concept Representation systems are being developed. Although these provide for a detailed conceptual representation of the underlying information, they have to be translated back to natural language for used by end-users and applications. The GALEN programme has been developing one such representation and we report here on a tool developed to generate natural language phrases from the GALEN conceptual representations. This tool can be adapted to different source modelling schemes and to different destination languages or sublanguages of a domain. It is based on a multilingual approach to natural language generation, realised through a clean separation of the domain model from the linguistic model and their link by well defined structures. Specific knowledge structures and operations have been developed for bridging between the modelling 'style' of the conceptual representation and natural language. Using the example of the scheme developed for modelling surgical operative procedures within the GALEN-IN-USE project, we show how the generator is adapted to such a scheme. The basic characteristics of the surgical procedures scheme are presented together with the basic principles of the generation tool. Using worked examples, we discuss the transformation operations which change the initial source representation into a form which can more directly be translated to a given natural language. In particular, the linguistic knowledge which has to be introduced--such as definitions of concepts and relationships is described. We explain the overall generator strategy and how particular transformation operations are triggered by language-dependent and conceptual parameters. Results are shown for generated French phrases corresponding to surgical procedures from the urology domain.

Linguistics↗

PubMedDate not supplied

An integrated hospital information system in Geneva.

Since the initial design phase from 1971 to 1973, the DIOGENE hospital information system at the University Hospital of Geneva has been treated as a whole and has retained its architectural unity, despite the need for modification and extension over the years. In addition to having a centralized patient database with the mechanisms for data protection and recovery of a transaction-oriented system, the DIOGENE system has a centralized pool of operators who provide support and training to the users; a separate network of remote printers that provides a telex service between the hospital buildings, offices, medical departments, and wards; and a three-component structure that avoids barriers between administrative and medical applications. In 1973, after a 2-year design period, the project was approved and funded. The DIOGENE system has led to more efficient sharing of costly resources, more rapid performance of administrative tasks, and more comprehensive collection of information about the institution and its patients.

Computer Systems↗