Ontology for General Medical Science


The OGMS ontology draws on:


Richard H. Scheuermann, Werner Ceusters, and Barry Smith, “Toward an Ontological Treatment of Disease and Diagnosis”, Proceedings of the 2009 AMIA Summit on Translational Bioinformatics, 2009, 116-120.

Many existing biomedical vocabulary standards rest on incomplete, inconsistent or confused accounts of basic terms pertaining to diseases, diagnoses, and clinical phenotypes. Here we outline what we believe to be a logically and biologically coherent framework for the representation of such entities and of the relations between them. We defend a view of disease as involving in every case some physical basis within the organism that bears a disposition toward the execution of pathological processes. We present our view in the form of a list of terms and definitions designed to provide a consistent starting point for the representation of both disease and diagnosis in information systems in the future.

This paper in turn draws on the following:

Cornelius Rosse, Anand Kumar, Jose LV Mejino Jr, Daniel L Cook, Landon T Detwiler and Barry Smith, A Strategy for Improving and Integrating Biomedical Ontologies, Proceedings of AMIA Symposium 2005, Washington DC, 639–643.

The integration of biomedical terminologies is indispensable to the process of information integration. When terminologies are linked merely through the alignment of their leaf terms, however, differences in context and ontological structure are ignored. Making use of the SNAP and SPAN ontologies, we show how three reference domain ontologies can be integrated at a higher level, through what we shall call the OBR framework (for: Ontology of Biomedical Reality). OBR is designed to facilitate inference across the boundaries of domain ontologies in anatomy, physiology and pathology.

Barry Smith, Werner Ceusters, Anand Kumar and Cornelius Rosse, “On Carcinomas and Other Pathological Entities”, Comparative and Functional Genomics, 2005:6(7); 379-387.

Tumors, abscesses, cysts, scars, fractures are familiar types of what we shall call pathological continuant entities. The instances of such types exist always in or on anatomical structures, which thereby become transformed into pathological anatomical structures of corresponding types: a fractured tibia, a blistered thumb, a carcinomatous colon. In previous work on biomedical ontologies we showed how the provision of formal definitions for relations such as is_a, part_of and transformation_of can facilitate the integration of such ontologies in ways which have the potential to support new kinds of automated reasoning. We here extend this approach to the treatment of pathologies, focusing especially on those pathological continuant entities which arise when organs become affected by carcinomas.

Includes a revised and corrected classification of biomedical entities. 

Anand Kumar, Yum Lina Yip, Barry Smith, Pierre Grenon, “Bridging the Gap between Medical and Bioinformatics: An Ontological Case Study in Colon Carcinoma”,Computers in Biology and Medicine, 2006; 36, (7-8): 694-711.

Ontological principles are needed in order to bridge the gap between medical and biological information in a robust and computable fashion. This is essential in order to draw inferences across the levels of granularity which span medicine and biology, an example of which include the understanding of the roles of tumor markers in the development and progress of carcinoma. Such information integration is also important for the integration of genomics information with the information contained in the electronic patient records in such a way that real time conclusions can be drawn. In this paper we describe a large multi-granular datasource built by using ontological principles and focusing on the case of colon carcinoma.

Anand Kumar and Barry Smith, “Oncology Ontology in the NCI Thesaurus”, AIME 2005 (Artificial Intelligence in Medicine Europe), (Lecture Notes in Computer Science 3581), 213–220.

The National Cancer Institute’s Thesaurus (NCIT) has been created with the goal of providing a controlled vocabulary which can be used by specialists in the various sub-domains of oncology. It is intended to be used for purposes of annotation in ways designed to ensure the integration of data and information deriving from these various sub-domains, and thus to support more powerful cross-domain inferences. In order to evaluate its suitability for this purpose, we examined the NCIT’s treatment of the kinds of entities which are fundamental to an ontology of colon carcinoma. We here describe the problems we uncovered concerning classification, synonymy, relations and definitions, and we draw conclusions for the work needed to establish the NCIT as a referenceontology for the cancer domain in the future.

Anand Kumar, Y. Lina Yip, Barry Smith, Dirk Marwede, Daniel Novotny, “An Ontology for Carcinoma Classification for Clinical Bioinformatics”, Medical Informatics Europe (MIE 2005), Geneva, 635–640.

There are a number of existing classifications and staging schemes for carcinomas, one of the most frequently used being the TNM classification. Such classifications represent classes of entities which exist at various anatomical levels of granularity. We argue that in order to apply such representations to the Electronic Health Records one needs sound ontologies which take into consideration the diversity of the domains which are involved in clinical bioinformatics. Here we outline a formal theory for addressing these issues in a way that the ontologies can be used to support inferences relating to entities which exist at different anatomical levels of granularity. Our case study is the colon carcinoma, one of the most common carcinomas prevalent within the European population.