Ebook: Ontologies in Medicine
It is generally acknowledged by the scientific community that ontologies may give a significant contribution to the design and implementation of better and more interoperable information systems, also in medicine. However, there is still much skepticism on the real impact that ontologies - apart from the academic world - may have on the design and maintenance of working information systems. The aim of this book is both to review fundamental theoretical issues on ontologies and to demonstrate the effectiveness of the ontological approach by illustrating real case studies. The first paper shows the usefulness of an ontological approach for solving some problems arising in medicine. It points out the relevance of terminological ontologies for disambiguating polysemous terms, for re-organizing very large corpora and detecting possible inconsistencies and for managing a catalog of bio-medical equipments. It also emphasizes the fundamental role played by ontologies when integration and interoperability of heterogeneous knowledge sources is needed, in particular in the field of clinical guidelines and evidence-based medicine. Other papers are a clear and relevant contribution to the topic of formal ontology in medicine: One introduces the application of the “descriptions and situations” theory in biomedicine. The others emphasize the important role of ontologies in modeling clinical guidelines: a crucial issue in healthcare management today. Two other interesting applications are in the field of genomics, the organ transplantation domain and where mistakes in medical ontologies come from and how they can be detected.
It is generally acknowledged by the scientific community that ontologies might make a significant contribution to the design and implementation better and more interoperable information systems, also in medicine. However, outside the academic world there is still much skepticism about the real impact that ontologies may have on the design and maintenance of working information systems.
The aim of this book is both to review fundamental theoretical issues on ontologies and to demonstrate the effectiveness of the ontological approach by illustrating real case studies.
The first paper (by Pisanelli and Gangemi) show the usefulness of an ontological approach for solving some problems arising in medicine. It points out the relevance of terminological ontologies for disambiguating polysemous terms, for re-organizing very large corpora and detecting possible inconsistencies and for managing a catalog of biomedical equipment. It also emphasizes the fundamental role played by ontologies when integration and interoperability of heterogeneous knowledge sources is needed, in particular in the field of clinical guidelines and evidence-based medicine.
The next couple of papers (by Smith and colleagues) are a clear and relevant contribution to the topic of formal ontology in medicine: The paper by Gangemi and coworkers introduces the application of the “descriptions and situations” theory in biomedicine.
The following two papers (by Kumar, Smith et al.) emphasize the important role of ontologies in modelling clinical guidelines: a crucial issue in health-care management today. Two other interesting applications are presented in the following: one by Martucci, Masseroli and Pinciroli in the field of genomics and the other by Burgun and colleagues in the organ transplantation domain.
Last but not least, Ceusters and co-workers show where mistakes in medical ontologies come from and how they can be detected.
This volume collects the research presented at a workshop that was held in Rome in October 2003. The workshop was jointly organized by the Laboratory of Applied Ontology of the Institute of Cognitive Science and Technology of the Italian National Research Council (www.loa-cnr.it) and by the Institute for Formal Ontology and Medical Information Science (ifomis.de ). The high quality of the papers presented and the liveliness of the discussions that followed made the event a successful meeting.
My only regret is that my great friend Riccardo Maceratini – a surgeon who was enthusiastic about the progress of medical informatics – could not attend it. He passed away too soon, and I am sure I am not the only one who would have enjoyed his presence at this workshop.
Domenico M. Pisanelli
Laboratory of Applied Ontology, CNR-ISTC, Viale Marx 15, 00137 Rome, Italy
In this paper we show the usefulness of an ontological approach for solving some problems arising in medicine. We point out the relevance of terminological ontologies for disambiguating polysemous terms, for re-organizing very large corpora and detecting possible inconsistencies and for managing a catalog of bio-medical equipments. We also put in evidence the fundamental role played by ontologies when integration and interoperability of heterogeneous knowledge sources is needed, in particular in the field of clinical guidelines and evidence-based medicine.
We propose a modular formal ontology of the biomedical domain with two components, one for biological objects, corresponding broadly to anatomy, and one for biological processes, corresponding broadly to physiology. The result constitutes what might be described as a joint venture between two perspectives – of so-called three-dimensionalism and four-dimensionalism – which are normally regarded as incompatible. We outline an approach which allows them to be combined together, and provide examples of its application in biomedicine.
The human body is a system made of systems. The body is divided into bodily systems proper, such as the endocrine and circulatory systems, which are subdivided into many sub-systems at a variety of levels, whereby all systems and subsystems engage in massive causal interaction with each other and with their surrounding environments. Here we offer an explicit definition of bodily system and provide a framework for understanding their causal interactions. Medical sciences provide at best informal accounts of basic notions such as system, process, and function, and while such informality is acceptable in documentation created for human beings, it falls short of what is needed for computer representations. In our analysis we will accordingly provide the framework for a formal definition of bodily system and of associated notions.
Formal ontology has proved to be an extremely useful tool for negotiating intended meaning, for building explicit, formal data sheets, and for the discovery of novel views on existing data structures. This paper describes an example of application of formal ontological methods to the creation of biomedical ontologies. Addressed here is the ambiguous notion of inflammation, which spans across multiple linguistic meanings, multiple layers of reality, and multiple details of granularity. We use UML class diagrams, description logics, and the DOLCE foundational ontology, augmented with the Description and Situation theory, in order to provide the representational and ontological primitives that are necessary for the development of detailed, flexible, and functional biomedical ontologies. An ontology design pattern is proposed as a modelling template for inflammations.
Evidence-based medicine relies on the execution of clinical practice guidelines and protocols. A great deal of effort has been invested in the development of tools which can automate the representation and execution of the recommendations contained within such guidelines, by creating Computer Interpretable Guideline Models (CIGMs). Context-based task ontologies (CTOs), based on standard terminology systems like UMLS, form one of the core components of such models. We have created DAML+OIL-based CTOs for the tasks referred to in the WHO guideline for hypertension management, drawing comparisons also with other, related guidelines. The advantages of CTOs include: contextualization of ontologies, tailoring of ontologies to specific aspects of the phenomena of interest, division of the complex tasks involved in creating ontologies into different levels, and provision of a methodology by means of which the task recommendations contained within guidelines can be integrated into the clinical practices of a health care set-up.
The paper presents the outlines of an ontology of plans and guidelines, which is then used as the basis for a framework for implementing guideline-based systems for the management of workflow in health care organizations. The framework has a number of special features, above all in that it enables us to represent in formal terms assignments of work-items both to individuals and to teams and to tailor guideline to specific contexts of application in health care organizations. It is designed also to enable implementations to do justice to the fact that the processes carried out in health care organizations may deviate in different ways from the norms set forth in corresponding guideline definitions. This means that implementations built in conformity with the framework will be marked by a type of flexibility that might make them more likely to be accepted by healthcare professionals than are standard guideline-based management systems.
While a massive amount of biomolecular information is increasingly accumulating in different databanks, on the other hand high-throughput technologies are generating a great quantity of data that need to be annotated with the genomic information available, and interpreted. To this aim, the use of specific ontologies can greatly help either in integrating different information stored within heterogeneous databanks, or in identifying and clustering sequence data sharing common characteristics. In the molecular biology domain, the Gene Ontology (GO) is the most developed and widely used ontology. To demonstrate its great utility in the annotation and biological interpretation of gene sets obtained by means of high-throughput experiments, we implemented the web application here described. It enables functional annotations of a given gene set on a genomic scale and across different species. Within our application the annotations provided by the GO vocabulary allow either to easily bind several information from different resources, or to cluster annotated genes according to their biological characteristics. Through the GO structure it is also possible to represent biological concepts with different specificity levels, from very general to very precise concepts. Furthermore, the statistical evaluation of the categorizations provided by the GO annotations enables to highlight the most significant biological characteristics of a gene set, and therefore to mine knowledge from data. Our created tool meets the need to manage a vast quantity of biological data with a simple user interface adapt also for users with limited informatics knowledge, leading them to evaluate the functional significance of experiment's results with graphical views and statistical indexes in a well-known web browser user interface.
Semantic heterogeneity is a key issue in the deployment of medical applications. In this paper, we examine solutions to address semantic heterogeneity for a complex organ transplantation information system. The information system that has been developed by the French agency for transplantation (EfG) has to gather medical information concerning patients and donors for organ allocation, epidemiological studies, and public health decisions. We analyze in this context the limits of the traditional approach based on a standard vocabulary and a relational database for the transplantation domain. We present its evolution towards a system that combines a terminology server and a data warehouse. The perspective is now to build a formal ontology that may support semantic integration in an advanced transplantation information system. Two open issues in formal ontology design are discussed. First, providing definitions of all medical concepts is not an obvious task if we want those definitions be meaningful, formal, and compatible with other ontologies. Second, propagation of properties along relations raises the needs for extending description logics with rules.
We present the details of a methodology for quality assurance in large medical terminologies and describe three algorithms that can help terminology developers and users to identify potential mistakes. The methodology is based in part on linguistic criteria and in part on logical and ontological principles governing sound classifications. We conclude by outlining the results of applying the methodology in the form of a taxonomy different types of errors and potential errors detected in SNOMED-CT®