Evaluating the process of online health information searching: a qualitative approach to exploring consumer perspectives.

Background: The Internet is a common resource that patients and consumers use to access health-related information. Multiple practical, cultural, and socioeconomic factors influence why, when, and how people utilize this tool. Improving the delivery of health-related information necessitates a thorough understanding of users' searching-related needs, preferences, and experiences.

Incorporating expert terminology and disease risk factors into consumer health vocabularies.

It is well-known that the general health information seeking lay-person, regardless of his/her education, cultural background, and economic status, is not as familiar with-or comfortable using-the technical terms commonly used by healthcare professionals. One of the primary reasons for this is due to the differences in perspectives and understanding of the vocabulary used by patients and providers even when referring to the same health concept. To bridge this "knowledge gap," consumer health vocabularies are presented as a solution.

Scalable representations of diseases in biomedical ontologies.

Background: The realm of pathological entities can be subdivided into pathological dispositions, pathological processes, and pathological structures. The latter are the bearer of dispositions, which can then be realized by their manifestations - pathologic processes. Despite its ontological soundness, implementing this model via purpose-oriented domain ontologies will likely require considerable effort, both in ontology construction and maintenance, which constitutes a considerable problem for SNOMED CT, presently the largest biomedical ontology.

The ACGT Master Ontology and its applications--towards an ontology-driven cancer research and management system.

Objective: This paper introduces the objectives, methods and results of ontology development in the EU co-funded project Advancing Clinico-genomic Trials on Cancer-Open Grid Services for Improving Medical Knowledge Discovery (ACGT). While the available data in the life sciences has recently grown both in amount and quality, the full exploitation of it is being hindered by the use of different underlying technologies, coding systems, category schemes and reporting methods on the part of different research groups. The goal of the ACGT project is to contribute to the resolution of these problems by developing an ontology-driven, semantic grid services infrastructure that will enable efficient execution of discovery-driven scientific workflows in the context of multi-centric, post-genomic clinical trials.