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Biomedical subjects

M Fieschi

Publications and source records attributed to M Fieschi.

At least 55 records · Page 3Linked to original sources
PubMed1996

Methodology for using the UMLS as a background knowledge for the description of surgical procedures.

The Unified Medical Language System (UMLS) contains and organizes a large number of terms from a variety of biomedical terminology systems. This study examines the relevance of the UMLS content and structures to the specific purpose of the conceptual representation of medical procedures. The MAOUSSC modelling is a compositional formalism with a description of elementary procedures in terms of elementary concept entities and combinations of such descriptions into more complex ones. The UMLS knowledge base is expected to provide semantically categorized medical concepts and interconcept relations. A method to reuse the UMLS has been developed. Quantitative and qualitative results are presented. Some difficulties in reusing the UMLS as a background knowledge are related to the preeminence of some terminology sources and to the instanciation of interconcept links. Other ones suggest that purpose-independence in categorization cannot be achieved.

Artificial Intelligence↗
PubMed1996

The project ARIANE: conceptual queries to information databases.

As information databases we consider all the collections of data records indexed by key-words, stored and delivered by computer systems. In previous research works we demonstrated the interest to design a conceptual model, in the conceptual graphs formalism, and to implement a computational model for information retrieval in large information databases. These models are based on the UMLS knowledge sources. This paper reminds briefly these models and describes tests done in querying a patients database and a bibliographical database.

Databases, Bibliographic↗
PubMed1996

[Top-Forum: an interactive multimedia knowledge database to improve quality of care in pediatric oncology].

The treatment of pediatric cancer patients is characterised by complex and aggressive chemotherapy, difficult decision making, the numerous protocols available and the necessity of highly skilled caregivers. Quality of care is a major issue in all pediatric oncology units. We created an interactive multi-media database available to each caregiver to permit him/her to have easy access to information and thus increase his/her knowledge and participate in increasing their group's know-how. The computer database is available to all on a free-access basis in each ward. This is a novel approach to quality care, as it accords great importance to personal formation, allowing each caregiver to broaden his/her knowledge via easily obtained data which he/she can help enrich by permanent feedback. This database may become the backbone of department know-how.

Adolescent↗
PubMed1995

Knowledge acquisition from the UMLS sources: application to the description of surgical procedures.

The re-usability of lexicons and knowledge in medicine is a crucial challenge. The Unified Medical Language System (UMLS) project has attempted to provide a repository of concepts, semantically categorized for biomedical domain. This paper describes some results about the relevance of UMLS structures for specific purposes. We have focused on the description of surgical procedures. Discussion concerns synonymy of terms, granularity of concepts, and ontology. A preliminary work on the exploitation of interconcept links by a computerized application reveals a heterogeneous implementation of those relationships. However, the UMLS provides a powerful knowledge base for developers.

General Surgery↗
PubMed1995

A conceptual graphs modeling of UMLS components.

The Unified Medical Language System (UMLS) of the U.S. National Library of Medicine is a complex collection of terms, concepts, and relationships derived from standard classifications. Potential applications would benefit from a high level representation of its components. This paper proposes a conceptual representation of both the Metathesaurus and the Semantic Network of the UMLS based on conceptual graphs. It shows that the addition of a dictionary of concepts to the UMLS knowledge base allows the capability to exploit it pertinently. This dictionary defines more precisely the core concepts and adds constraints on their use. Constraints are dedicated to guide an "intelligent" browsing of the UMLS knowledge sources.

Dictionaries as Topic↗
PubMed1995

Handling information and knowledge in the FORUM hypermedia authoring system: application to uterine magnetic resonance imaging.

Hypertext and hypermedia are used to access loosely structured information. The lack of conceptual model for hypertext application makes it difficult to represent the mental model of the author. Users are often lost in the information and the objective of the author is not achieved. In this paper, we describe an approach to handle information and knowledge in the FORUM hypermedia authoring system. It allows the author to create and maintain the hypertext more easily and facilitates the navigation of the reader. An application for learning uterine magnetic resonance imaging is also presented.

Computer Systems↗
PubMed1995

Decision support systems from the standpoint of knowledge representation.

Relationships between decision-support systems and knowledge representation are examined from three different points of view: the characteristics of medical decisions that might influence the selection of appropriate knowledge representations,--the extent to which different knowledge representations can support efficient medical decisions and,--the validation of knowledge hypotheses through the practice of decision support systems. A three-level model of knowledge representation is proposed that includes a contextual, a conceptual and a computational level. Taking into consideration the context that leads to the selection of a given representation raises the issue of multiexpertise and multirepresentation modeling. Implementation of decision support systems as sets of cooperative agents and integration in the health information systems are considered.

Artificial Intelligence↗
PubMed1994

Users conceptual views on medical information databases.

As information databases we consider all the kinds of information repositories that are handled by computer systems. When querying very large information databases, the end-users are often faced with the problem to parse their questions efficiently into the query languages of the computer systems. Conceptual graphs were initially designed for natural language analysis and understanding. Due to their closeness to semantic networks, their expressiveness is powerful enough to be applied to knowledge representation and use by computer systems. This work demonstrates that conceptual graphs are a suitable means to model both the information in patient databases and the queries to these databases, and that operations on graphs can compute the pattern matching process needed to provide the answers. A prototype that exploits this model is presented. Experiments have been made with the material furnished by the Unified Medical Language System project (version 2, 1992) of the National Library of Medicine, USA.

Abstracting and Indexing↗
PubMed1994

A computational model of information retrieval with UMLS.

A high level representation of data would clarify the complex collection of medical concepts, terms and relationships derived from standard classifications that the Unified Medical Language System contains. A conceptual model is described which represents the data structure. A second objective of this conceptual model is to provide users with the capability to build queries to information databases as easily as possible on the basis of this data structure. The methods used to build this model are semantic networks and conceptual graphs. The object-oriented computational model which implements this conceptual model is detailed. It reuses part of the generic C++ classes of the National Institutes of Health library. New classes are added to this library to implement the needed functionalities.

Information Storage and Retrieval↗
PubMed1994

Designing a sub-set of the UMLS knowledge base applied to a clinical domain: methods and evaluation.

The UMLS is a complex collection of interconnected biomedical concepts derived from standard nomenclatures. Designing a specific subset of the UMLS knowledge base relevant to a medical domain is a prerequisite for the development of specialized applications based on UMLS. We have developed a method based on the selection of the appropriate terms in original nomenclatures and the capture of a set of UMLS terms that are linked to them in the network to a certain degree. We have experimented it as the foundation for a concept base applied to urology. Results depend on the exhaustiveness of the relationships between the Metal concepts. A preliminary analysis of the sub-base reveals that some adaptations of vocabulary and ontology are required for clinical applications.

Algorithms↗
PubMed1994

[Evaluation of computer-assisted instruction methods. Apropos of 26 comparative studies published between 1989 and 1992].

Information and knowledge processing technologies have contributed to the development of Computer assisted instruction (CAI) applications. Multimedia technologies will increase the possibilities of these programmes in the future. However the evaluation of the software as well as the other technologies is necessary. The authors have tried to quantify the contributions of CAI analysing the literature referenced in MEDLINE from 1989 to 1992. On the 470 papers indexed with the key-word "Computer Assisted Instruction", 56 studies take evaluation into account. Only 26, that is 5.5%, presented a clear and explicit methodology of evaluation. On the 26 studies, 16 were considered with positive result and among these, 6 presented a statistical significance. The conditions and the criteria of the evaluation studies do not permit a meta analysis. Is is necessary to develop standardized evaluation criteria to estimate the quantitative and qualitative impact of the CAI technics on the educational process and their own pedagogical contribution.

Computer-Assisted Instruction↗
PubMed1993

[Analysis of parameters used for the evaluation of the Relative Complexity Index beta].

The Relative Complexity Index beta (RCI beta) has been devised as an indicator of the relative complexity and cost of anaesthesia. It takes into account the type of anaesthesia, the duration, the type of surgery and the patients' ASA status. This study analyses the relative weight of each component of RCI by a multiple regression analysis. The results show the pre-eminence of the surgical procedure in the formula. The weight of surgical procedure is responsible of 80 p. cent of the model's variance. In these conditions, the RCI beta cannot be accepted as an accurate complexity index of anaesthesia.

Anesthesia, General↗
PubMed1993

[Auto-training in radiology: the FORUM project applied to MRI of the uterus].

We describe the FORUM project which is a computer-assisted learning tool written with hypertext and hypermedia software emphasizing student interaction. This project is designed to allow the user to teach himself uterine Magnetic Resonance Imaging, which is a rapidly expanding technique with a wealth of specific findings. The program is currently available for Apple personal computers and is intended for beginners or confirmed radiologists and gynaecologists.

Computer User Training↗
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↗
PubMed1993

A conceptual model for information retrieval with UMLS.

Information retrieval in large information databases is a non-deterministic process which needs a sequence of search steps generally. One of the main problems to which the end-users are faced is to parse efficiently their questions into the query language that the computer systems allow. Conceptual graphs were initially designed for natural language analysis and understanding. Due to their closeness to semantic networks, their expressiveness is powerful enough to be applied to knowledge representation and use by computer systems. This work demonstrates that conceptual graphs are a suitable means to model the end-users querieson the basis of the thesaurus and the semantic network of the UMLS project.

Information Storage and Retrieval↗
PubMed1990

Towards validation of expert systems as medical decision aids.

Expert system evaluation is an important step in knowledge engineering development and is clearly not a simple process. The aim of this paper is to introduce methodological aspects of medical knowledge base validation. We distinguish two components of the evaluation: verification and validation. In the first part, the difficulties of evaluation are analysed, problems with some techniques used in the evaluation process are discussed. In the second part, our experiment gives guidelines to present these aspects and underline what and when to evaluate.

Decision Making, Computer-Assisted↗
PubMed1986

Expert systems for medical consultation.

After reviewing some of the elements that permit a clearer understanding of what characterizes the "expert systems" approach, representation of medical concepts, symbolic manipulation rather than numeric calculation, causal reasoning, etc., this paper will try to deal with some of the most noteworthy developments in medical decision aid, teaching, research, before discussing some problems raised by the evaluation of expert systems in medicine.

Artificial Intelligence↗