39 research outputs found
An ontology segmentation tool
Extracting a minimal relevant segment of an extensive domain ontology is an often recurring problem in ontology engineering. We present a software solution to this problem that is the combination of an ontology-independent user interface generator and a module implementing an ontology segmentation algorithm. We describe the algorithm and compare it with other ontology segmentation methods proposed in the literature
Telemedicine
Telemedicine is a rapidly evolving field as new technologies are implemented for example for the development of wireless sensors, quality data transmission. Using the Internet applications such as counseling, clinical consultation support and home care monitoring and management are more and more realized, which improves access to high level medical care in underserved areas. The 23 chapters of this book present manifold examples of telemedicine treating both theoretical and practical foundations and application scenarios
An ontology for formal representation of medication adherence-related knowledge : case study in breast cancer
Indiana University-Purdue University Indianapolis (IUPUI)Medication non-adherence is a major healthcare problem that negatively impacts
the health and productivity of individuals and society as a whole. Reasons for medication
non-adherence are multi-faced, with no clear-cut solution. Adherence to medication
remains a difficult area to study, due to inconsistencies in representing medicationadherence
behavior data that poses a challenge to humans and today’s computer
technology related to interpreting and synthesizing such complex information.
Developing a consistent conceptual framework to medication adherence is needed to
facilitate domain understanding, sharing, and communicating, as well as enabling
researchers to formally compare the findings of studies in systematic reviews.
The goal of this research is to create a common language that bridges human and
computer technology by developing a controlled structured vocabulary of medication
adherence behavior—“Medication Adherence Behavior Ontology” (MAB-Ontology)
using breast cancer as a case study to inform and evaluate the proposed ontology and
demonstrating its application to real-world situation. The intention is for MAB-Ontology
to be developed against the background of a philosophical analysis of terms, such as
belief, and desire to be human, computer-understandable, and interoperable with other
systems that support scientific research.
The design process for MAB-Ontology carried out using the METHONTOLOGY
method incorporated with the Basic Formal Ontology (BFO) principles of best practice.
This approach introduces a novel knowledge acquisition step that guides capturing medication-adherence-related data from different knowledge sources, including
adherence assessment, adherence determinants, adherence theories, adherence
taxonomies, and tacit knowledge source types. These sources were analyzed using a
systematic approach that involved some questions applied to all source types to guide
data extraction and inform domain conceptualization. A set of intermediate
representations involving tables and graphs was used to allow for domain evaluation
before implementation. The resulting ontology included 629 classes, 529 individuals, 51
object property, and 2 data property.
The intermediate representation was formalized into OWL using Protégé. The
MAB-Ontology was evaluated through competency questions, use-case scenario, face
validity and was found to satisfy the requirement specification. This study provides a
unified method for developing a computerized-based adherence model that can be
applied among various disease groups and different drug categories