VO: Vaccine Ontology

Vaccine research, as well as the development, testing, clinical trials, and commercial uses of vaccines involve complex processes with various biological data that include gene and protein expression, analysis of molecular and cellular interactions, study of tissue and whole body responses, and extensive epidemiological modeling. Although many data resources are available to meet different aspects of vaccine needs, it remains a challenge how we are to standardize vaccine annotation, integrate data about varied vaccine types and resources, and support advanced vaccine data analysis and inference. To address these problems, the community-based Vaccine Ontology (VO, "http://www.violinet.org/vaccineontology":http://www.violinet.org/vaccineontology) has been developed through collaboration with vaccine researchers and many national and international centers and programs, including the National Center for Biomedical Ontology (NCBO), the Infectious Disease Ontology (IDO) Initiative, and the Ontology for Biomedical Investigations (OBI). VO utilizes the Basic Formal Ontology (BFO) as the top ontology and the Relation Ontology (RO) for definition of term relationships. VO is represented in the Web Ontology Language (OWL) and edited using the Protégé-OWL. Currently VO contains more than 2000 terms and relationships. VO emphasizes on classification of vaccines and vaccine components, vaccine quality and phenotypes, and host immune response to vaccines. These reflect different aspects of vaccine composition and biology and can thus be used to model individual vaccines. More than 200 licensed vaccines and many vaccine candidates in research or clinical trials have been modeled in VO. VO is being used for vaccine literature mining through collaboration with the National Center for Integrative Biomedical Informatics (NCIBI). Multiple VO applications will be presented.
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VO: Vaccine Ontology

The collaborative, community-based Vaccine Ontology (VO) was developed to promote vaccine data standardization, integration, and computer-assisted reasoning. Currently VO covers a variety of aspects of the vaccine domain, with an emphasis on classification of vaccines and vaccine components, and on host immune response to vaccines. VO can be used for a number of applications, e.g., ontology-based vaccine literature mining through collaboration with the National Center for Integrative Biomedical Informatics (NCIBI)

Accuracy of telepsychiatric assessment of new routine outpatient referrals

<p>Abstract</p> <p>Background</p> <p>Studies on the feasibility of telepsychiatry tend to concentrate only on a subset of clinical parameters. In contrast, this study utilises data from a comprehensive assessment. The main objective of this study is to compare the accuracy of findings from telepsychiatry with those from face to face interviews.</p> <p>Method</p> <p>This is a primary, cross-sectional, single-cluster, balanced crossover, blind study involving new routine psychiatric referrals. Thirty-seven out of forty cases fulfilling the selection criteria went through a complete set of independent face to face and video assessments by the researchers who were blind to each other's findings.</p> <p>Results</p> <p>The accuracy ratio of the pooled results for DSM-IV diagnoses, risk assessment, non-drug and drug interventions were all above 0.76, and the combined overall accuracy ratio was 0.81. There were substantial intermethod agreements for Cohen's kappa on all the major components of evaluation except on the Risk Assessment Scale where there was only weak agreement.</p> <p>Conclusion</p> <p>Telepsychiatric assessment is a dependable method of assessment with a high degree of accuracy and substantial overall intermethod agreement when compared with standard face to face interview for new routine outpatient psychiatric referrals.</p

Accuracy of telepsychiatric assessment of new routine outpatient referrals-0

<p><b>Copyright information:</b></p><p>Taken from "Accuracy of telepsychiatric assessment of new routine outpatient referrals"</p><p>http://www.biomedcentral.com/1471-244X/7/55</p><p>BMC Psychiatry 2007;7():55-55.</p><p>Published online 5 Oct 2007</p><p>PMCID:PMC2194760.</p><p></p>crossed are drop-outs