Comprehensive Overview of Decision-Fusion Technique in Healthcare: A Scoping Review Protocol
Journal: Frontiers in Health Informatics (Vol.7, No. 1)Publication Date: 2018-01-01
Authors : Nazari E Pour R Tabesh H;
Page : 34-37
Keywords : Decision fusion; Decision making; Health care; Medicine;
Abstract
Introduction: In recent decades, the use of Decision-Fusion techniques has attracted the attention of many scholars and academics. The use of this technique to manage challenges such as diversity and scalability in the Big Data is very common in various industries, including the health care industry. Hence, a comprehensive review of studies on the use of this technique in the field of health care and its review of the types of applied methods, the type of used data, the obtained data, the use and purpose of technique can be useful. Therefore, the protocol of this Scope Review article will be presented to examine this technique in the field of health care. Material and Methods: The protocol was designed based on O'Malley and Arksey's five-step framework in combination with Levac and colleages' enhancement. First, a field-specific structure was defined for study. This structure consists of three main aspects: the purpose and hypothesis, modeling, model achievements. Considering this structure, the 5-step framework was created for the study. Three databases, PubMed, science direct, and EMBASE were selected for search and an appropriate strategy for incorporating health related articles that utilized this technique was used. Data was extracted based on defined aspects, and categories were created based on their frequency. To analyze the extracted data from articles, frequency analysis, descriptive statistical methods and qualitative thematic analysis will be used. Results: This paper is the first study of Scope Review regarding the use of Decision-Fusion technology in health care. Reference frame questions aspects are designed as field-specific. To clarify the research questions, O'Malley Arksey's five-step framework was used in combination with Levac et al.enhancement. A classify scheme for the category of the aspects [for the categorization of the dimensions] was presented based on the frequency of their values Conclusion: A classify scheme for the category of the aspects [for the categorization of the dimensions] was presented based on the frequency of their values.
Other Latest Articles
- Diagnosis of Brain Tumor Using Combination of K-Means Clustering and Genetic Algorithm
- Comparative Study of Data Elements and Data Analysis Methods in Myocardial Infarction Registry in Selected Countries and Iran
- Predictions of Laryngeal Cancer Using Neural Network in Kerman Shafa Hospital
- Designing and Evaluating of a Guideline-Based Recommender-Interpreter System to Inform Diabetic Patients about the Status of Periodic Lab Tests
- Semantic Web: A Context for Medical Knowledge Discovering and Sharing
Last modified: 2018-12-11 00:59:03