Biomedical subjects

L P Seka

Publications and source records attributed to L P Seka.

7 recordsLinked to original sources

PubMed1997

A network of web multimedia medical information servers for a medical school and university hospital.

Modern medicine requires a rapid access to information including clinical data from medical records, bibliographic databases, knowledge bases and nomenclature databases. This is especially true for University Hospitals and Medical Schools for training as well as for fundamental and clinical research for diagnosis and therapeutic purposes. This implies the development of local, national and international cooperation which can be enhanced via the use and access to computer networks such as Internet. The development of professional cooperative networks goes with the development of the telecommunication and computer networks and our project is to make these new tools and technologies accessible to the medical students both during the teaching time in Medical School and during the training periods at the University Hospital. We have developed a local area network which communicates between the School of Medicine and the Hospital which takes advantage of the new Web client-server technology both internally (Intranet) and externally by access to the National Research Network (RENATER in France) connected to the Internet network. The address of our public web server is http:(/)/www.med.univ-rennesl.fr.

Artificial Intelligence↗

PubMed1997

Computer assisted medical diagnosis using the Web.

The ADM (Aide au diagnostic Medical) project was started 15 years ago and was the first telematic project for physicians in France using the MINITEL terminal. The knowledge base contains information on more than 10000 diseases from all pathological fields, using more than 100000 signs or symptoms. The ADM system has two main functionalities for physicians: consultation of diseases descriptions and list of diseases containing one or more symptoms. The ADM knowledge base is supported by a relational database management system (DBMS ORACLE) and we developed a Web interface using the Perl language to produce HTML pages for the web server. We will describe our experience on redesigning a large existing medical knowledge base for diffusion on the web Internet.

Artificial Intelligence↗

PubMed1997

ADM-INDEX: an automated system for indexing and retrieval of medical texts.

ADM-INDEX is a system for indexing and retrieval of Patients Discharge Summaries (PDSs) by using linguistic methods (morphologic, syntaxic and semantic processing). The ADM-INDEX knowledge base is a restructuring of a diagnostic aid knowledge base (ADM) in order to allow the linguistic analysis of medical texts. The ADM system is a comprehensive medical knowledge base which has been developed since 1972 at the University Hospital of Rennes and which has been the first professional videotex medical diagnostic aid in France. After linguistic analysis, ADM-INDEX build the index table with thesaurus wording, medical words, concepts and phrases, unknown words contained in each PDS. The benefit of using those different elements is to improve information retrieval. Although our system is constructed with the ADM dictionary, it can be easily applied to other medical nomenclature or thesaurus. In this paper, we present on the one hand the ADM-INDEX knowledge base which is constituted by rules, a dictionary and a thesaurus, and on the other hand, the process of indexing and retrieval information.

Abstracting and Indexing↗

PubMed1997

[Value of automated medical indexing of an image database and a digital radiological library].

We indexed the contents of a radiology server on the web to facilitate access to research documents and to link reference texts to images contained in radiology databases. Indexation also allows case reports to be transformed with no supplementary work into formats compatible with computer-assisted training. Indexation was performed automatically by ADM-Index, the aim being to identify the medical concepts expressed within each medical text. Two types of texts were indexed: medical imaging reference books (Edicerf) and case reports with illustrations and captions (Iconocerf). These documents are now available on a web server with HTML format for Edicerf and on an Oracle database for Iconocerf. When the user consults a chapter of a book or a case report, the indexed terms are displayed in the heading; all reference texts and case reports containing the indexed terms can then be called up instantaneously. The user can express his search in natural language. Indexation follows the same process allowing instantaneous recall of all reference texts and case reports where the same concept appears in the diagnosis or clinical context. By using the context of the case reports as the search index, all case reports involving a common medical concept can be found. The context is interpreted as a question. When the user responds to this question, ADM-Index compares this response with the answer furnished by the reference texts and case reports. Correct or erroneous responses can thus be identified, converting the system into a computer-assisted training tool.

Abstracting and Indexing↗

PubMed1995

Automated coding of patient discharge summaries using conceptual graphs.

In medicine, as in other domains, indexing and classification is a natural human task which is used for information retrieval and representation. In the medical field, encoding of patient discharge summaries is still a manual time-consuming task. This paper describes an automated coding system of patient discharge summaries from the field of coronary diseases into the ICD-9-CM classification. The system is developed in the context of the European AIM MENELAS project, a natural-language understanding system which uses the conceptual-graph formalism. Indexing is performed by using a two-step processing scheme; a first recognition stage is implemented by a matching procedure and a secondary selection stage is made according to the coding priorities. We show the general features of the necessary translation of the classification terms in the conceptual-graph model, and for the coding rules compliance. An advantage of the system is to provide an objective evaluation and assessment procedure for natural-language understanding.

Artificial Intelligence↗

PubMedDate not supplied

A system that facilitates the orientation within procedure nomenclatures through a semantic approach.

The representation of medical concepts should provide the flexibility required to support several purposes. We have implemented a model in which medical terms are represented in a standard format based on a semantic description of the terms. We have focused on the description of procedures. Underlying this project is the assumption that information about medical procedures is crucial in the healthcare system. A prototype has been developed for urology. Because of the large number of terms in the Unified Medical Language System (UMLS) and the abundance of links between them, we have experimented in the use of the UMLS as the foundation for our concept base. We assess the usefulness of this approach and discuss its improvements.

Algorithms↗

PubMedDate not supplied

A first evaluation of a pedagogical network for medical students at the University Hospital of Rennes.

A pedagogical network has been developed at University Hospital of Rennes from 1996. The challenge is to give medical information and informatics tools to all medical students in the clinical wards of the University Hospital. At first, nine wards were connected to the medical school server which is linked to the Internet. Client software electronic mail and WWW Netscape on Macintosh computers. Sever software is set up on Unix SUN providing a local homepage with selected pedagogical resources. These documents are stored in a DBMS database ORACLE and queries can be provided by specialty, authors or disease. The students can access a set of interactive teaching programs or electronic textbooks and can explore the Internet through the library information system and search engines. The teachers can send URL and indexation of pedagogical documents and can produce clinical cases: the database updating will be done by the users. This experience of using Web tools generated enthusiasm when we first introduced it to students. The evaluation shows that if the students can use this training early on, they will adapt the resources of the Internet to their own needs.

Computer-Assisted Instruction↗