OWL model of clinical trial eligibility criteria compatible with partially-known information.

BACKGROUND: Clinical trials are important for patients, for researchers and for companies. One of the major bottlenecks is patient recruitment. This task requires the matching of a large volume of information about the patient with numerous eligibility criteria, in a logically-complex combination. Moreover, some of the patient's information necessary to determine the status of the eligibility criteria may not be available at the time of pre-screening. RESULTS: We showed that the classic approach based on negation as failure over-estimates rejection when confronted with partially-known information about the eligibility criteria because it ignores the distinction between a trial for which patient eligibility should be rejected and trials for which patient eligibility cannot be asserted. We have also shown that 58.64% of the values were unknown in the 286 prostate cancer cases examined during the weekly urology multidisciplinary meetings at Rennes' university hospital between October 2008 and March 2009.We propose an OWL design pattern for modeling eligibility criteria based on the open world assumption to address the missing information problem. We validate our model on a fictitious clinical trial and evaluate it on two real clinical trials. Our approach successfully distinguished clinical trials for which the patient is eligible, clinical trials for which we know that the patient is not eligible and clinical trials for which the patient may be eligible provided that further pieces of information (which we can identify) can be obtained. CONCLUSIONS: OWL-based reasoning based on the open world assumption provides an adequate framework for distinguishing those patients who can confidently be rejected from those whose status cannot be determined. The expected benefits are a reduction of the workload of the physicians and a higher efficiency by allowing them to focus on the patients whose eligibility actually require expertise.

Ontology driven decision support systems for medical diagnosis - an interactive form for consultation in patients with plasma cell disease.

Multiple myeloma (MM) is a malignant disorder characterized by the monoclonal proliferation of B cell derived plasma cells in the bone marrow. The diagnosis depends on the identification of abnormal monoclonal marrow plasma cells, monoclonal protein in the serum or urine, evidence of end-organ damage, and a clinical picture consistent with MM. The distinction between MM stages- monoclonal gammopathy of undetermined significance or indolent myeloma-is critical in guiding therapy. This paper describes how to produce ontology-driven semiological rules base (SRB) and a consultation form to aid in the diagnosis of plasma cells diseases. We have extracted the MM sub-ontology from the NCI Thesaurus. Using Protégé 3.4.2 and owl1, criteria in the literature for the diagnosis and staging of MM have been added to the ontology. All quantitative parameters have been transformed to a qualitative format. A formal description of MM variants and stages has been given. The obtained ontology has been checked by a reasoner and instantiated to obtain a SRB. The form created has been tested and evaluated utilizing 63 clinical medical reports. The likelihood for a disease being the correct diagnosis is determined by computing a ratio. The resulting tool is relevant for MM diagnosis and staging.

Automatic definition of the oncologic EHR data elements from NCIT in OWL.

UNLABELLED: Semantic interoperability based on ontologies allows systems to combine their information and process them automatically. The ability to extract meaningful fragments from ontology is a key for the ontology re-use and the construction of a subset will help to structure clinical data entries. The aim of this work is to provide a method for extracting a set of concepts for a specific domain, in order to help to define data elements of an oncologic EHR. METHOD: a generic extraction algorithm was developed to extract, from the NCIT and for a specific disease (i.e. prostate neoplasm), all the concepts of interest into a sub-ontology. We compared all the concepts extracted to the concepts encoded manually contained into the multi-disciplinary meeting report form (MDMRF). RESULTS: We extracted two sub-ontologies: sub-ontology 1 by using a single key concept and sub-ontology 2 by using 5 additional keywords. The coverage of sub-ontology 2 to the MDMRF concepts was 51%. The low rate of coverage is due to the lack of definition or mis-classification of the NCIT concepts. By providing a subset of concepts focused on a particular domain, this extraction method helps at optimizing the binding process of data elements and at maintaining and enriching a domain ontology.

Creating an ontology driven rules base for an expert system for medical diagnosis.

Expert systems of the 1980s have failed on the difficulties of maintaining large rule bases. The current work proposes a method to achieve and maintain rule bases grounded on ontologies (like NCIT). The process described here for an expert system on plasma cell disorder encompasses extraction of a sub-ontology and automatic and comprehensive generation of production rules. The creation of rules is not based directly on classes, but on individuals (instances). Instances can be considered as prototypes of diseases formally defined by "destrictions" in the ontology. Thus, it is possible to use this process to make diagnoses of diseases. The perspectives of this work are considered: the process described with an ontology formalized in OWL1 can be extended by using an ontology in OWL2 and allow reasoning about numerical data in addition to symbolic data.

BioQuali Cytoscape plugin: analysing the global consistency of regulatory networks.

BACKGROUND: The method most commonly used to analyse regulatory networks is the in silico simulation of fluctuations in network components when a network is perturbed. Nevertheless, confronting experimental data with a regulatory network entails many difficulties, such as the incomplete state-of-art of regulatory knowledge, the large-scale of regulatory models, heterogeneity in the available data and the sometimes violated assumption that mRNA expression is correlated to protein activity. RESULTS: We have developed a plugin for the Cytoscape environment, designed to facilitate automatic reasoning on regulatory networks. The BioQuali plugin enhances user-friendly conversions of regulatory networks (including reference databases) into signed directed graphs. BioQuali performs automatic global reasoning in order to decide which products in the network need to be up or down regulated (active or inactive) to globally explain experimental data. It highlights incomplete regions in the network, meaning that gene expression levels do not globally correlate with existing knowledge on regulation carried by the topology of the network. CONCLUSION: The BioQuali plugin facilitates in silico exploration of large-scale regulatory networks by combining the user-friendly tools of the Cytoscape environment with high-performance automatic reasoning algorithms. As a main feature, the plugin guides further investigation regarding a system by highlighting regions in the network that are not accurately described and merit specific study.

An Internet supported workflow for the publication process in UMVF (French Virtual Medical University).

The " Université Médicale Virtuelle Francophone" (UMVF) is a federation of French medical schools. Its main goal is to share the production and use of pedagogic medical resources generated by academic medical teachers. We developed an Open-Source application based upon a workflow system, which provides an improved publication process for the UMVF. For teachers, the tool permits easy and efficient upload of new educational resources. For web masters it provides a mechanism to easily locate and validate the resources. For librarian it provide a way to improve the efficiency of indexation. For all, the utility provides a workflow system to control the publication process. On the students side, the application improves the value of the UMVF repository by facilitating the publication of new resources and by providing an easy way to find a detailed description of a resource and to check any resource from the UMVF to ascertain its quality and integrity, even if the resource is an old deprecated version. The server tier of the application is used to implement the main workflow functionalities and is deployed on certified UMVF servers using the PHP language, an LDAP directory and an SQL database. The client tier of the application provides both the workflow and the search and check functionalities. A unique signature for each resource, was needed to provide security functionality and is implemented using a Digest algorithm. The testing performed by Rennes and Lille verified the functionality and conformity with our specifications.