Bayesian Ontologies in Spatial Integrating Medical Information Systems

2012 ◽  
pp. 220-232
Author(s):  
Stelios Zimeras
Keyword(s):  
Information Systems ◽  
Spatial Analysis ◽  
Geographical Information Systems ◽  
Medical Information ◽  
Graphical Representation ◽  
Current System ◽  
Methodological Approach ◽  
Disease Monitoring ◽  
Point Mapping ◽  
Accident Data

Geographical Information Systems (GIS) play a major role in all areas of health research, especially for the understanding of spatial variations concerning disease monitoring. The information produced by the spatial analysis can be modelled and displayed using maps. Spatial analysis (as an alternative statistical technique) may be used in order to suggest health patterns for describing the spreading of various diseases. Areas where GIS can be of benefit include the point mapping of patients and aggregated analyses within different geographical areas. The incorporation of GIS sections in Healthcare Information Systems aims towards the efficient and automated follow-up of prevalence of various diseases in diverse geographic regions. A very important feature of the current system is the integration of queries for the extraction of specific information regarding the above parameters. The queries have been developed through the ontologies of the system. Each ontology refers to each of the correlations that are being explored. The appropriate ontology design techniques have been used to assure the validity of the query output. This work describes the methodological approach for the development of a real time electronic health record, for the statistical analysis of geographic information and graphical representation for disease monitoring. Uncertainty of the ontology system may be achieved by proposing Bayesian type statistical techniques like Bayesian network and Markov logic. Implementation of the proposed techniques will be illustrated considering real accident data.

Intelligence from Space

2011 ◽  
pp. 194-226
Author(s):  
Paul Hendriks
Keyword(s):  
Decision Making ◽  
Information Systems ◽  
Spatial Analysis ◽  
Geographical Information Systems ◽  
Geographical Information ◽  
Specific Class ◽  
Step Procedure ◽  
Decision Making Processes ◽  
Projected Position ◽  
Spatial Element

The spatial element, which is omnipresent in data and information relevant to organizations, is much underused in the decision-making processes within organizations. This applies also to decision-making within the domain of Competitive Intelligence. The chapter explores how the CI function may benefit from developing a spatial perspective on its domain and how building, exploring and using this perspective may be supported by a specific class of information systems designed to handle the spatial element in data: Geographical Information Systems (GIS). The chapter argues that the key element for linking GIS to CI involves the identification of situations in which spatial analysis may support organizational decision-making within the CI domain. It presents a three-step procedure for identifying how CI may recognize spatial decision problems that are useful to boost the operation of the CI function. The first step concerns identifying relevant spatial variables, for instance by analyzing economic, demographic or political trends as to their spatial implications. The second step involves using GIS for positioning the organization with respect to the identified variables (present and projected position). The third step amounts to drawing strategic conclusions from Step 2 by assessing how the competition in relationship with the own organization would be positioned along the identified spatial analysis lines.

scholarly journals Aligning Partners in Pediatric Health: Using Geographical Information Systems to Plan Community Coalitions

2020 ◽  
Vol 11 ◽  
pp. 215013272094051
Author(s):  
Margaret B. Nguyen
Keyword(s):  
Primary Care ◽  
Information Systems ◽  
Spatial Analysis ◽  
Child Health ◽  
Geographical Information Systems ◽  
Pediatric Asthma ◽  
Geographical Information ◽  
Community Coalitions ◽  
Community Partners ◽  
Ed Visits

Introduction: Compared with adults, children have higher emergency department (ED) utilization for asthma exacerbation. While community coalitions have been shown to prevent ED visits for asthma, there is little guidance on where to best implement these efforts. Geographical information systems (GIS) technology can help in the selection and coordination of potential coalition partners. This report proposes a model to be used by clinicians and child health equity advocates to strategize high-impact community health interventions. The aims were to identify the clusters of ED utilization for pediatric asthma, evaluate sociodemographic features of the population within the clusters, and identify potential primary care and school community partners. Methods: This model uses ED visit data from 450 nonmilitary California hospitals in 2012. We obtained ZIP code–level counts and rates for patients younger than 18 years discharged with a diagnosis code of 493 for asthma conditions from the California Office of Statewide Health Planning and Development’s Open Portal. We applied GIS spatial analysis techniques to identify statistically significant cluster for pediatric asthma ED utilization. We then locate the candidate community partners within these clusters. Results: There were 181 720 ED visits for asthma for all age groups in 2012 with 70 127 visits for children younger than 18 years. The top 3 geographic clusters for ED utilization rates were located in Fresno, Inglewood, and Richmond City, respectively. Spatial analysis maps illustrate the schools located within 0.5– and 1-mile radii of primary care clinics and provide a visual and statistical description of the population within the clusters. Conclusion: This study demonstrates a model to help clinicians understand how GIS can aid in the selection and creation of coalition building. This is a potentially powerful tool in the addressing child health disparities.

scholarly journals Cartographic Analysis of the Geomorphological Hazards of the Eastern Part of Sheikh Saad Sub-District by Using GIS

2021 ◽  
Vol 11 (3) ◽  
Author(s):  
Hind Fadhil Ibrahim Al-Jubouri ◽  
Firas S Raheem ◽  
Prof Dr Osama K Abdulridah ◽  
Prof Dr Ali A Kazem
Keyword(s):  
Information Systems ◽  
Spatial Analysis ◽  
Geographical Information Systems ◽  
High Efficiency ◽  
Geographical Area ◽  
Three Dimensional ◽  
Geographical Information ◽  
3D Analysis ◽  
Automated Methods ◽  
Modern Technologies

Geographical information systems are the latest applied computer technologies that contribute to supporting contemporary geographical studies through the possibility of working on preparing a database of geographical phenomena and modeling them in a digital form by providing automated methods and a set of systems and programs for managing and processing data with spatial and non-spatial reference, which is one of the important functions in geographic information systems And the base on which it depends to reach the optimal decisions to reveal the spatial relationships and correlations between geographical phenomena and with high efficiency, to become the contemporary method in the method of processing and spatial analysis of geographical information instead of the old traditional methods of geographical analysis, and the system also allowed the geographical area to enter into the era of modern technologies to evaluate phenomena. Geographical forecasting. The research materials and methods are determined by adopting topographical and geological maps, land-sat satellite visuals, and DEM data to form the search database, and based on the GIS program (Arc Map 9.3) and the (Global Mepper 11) program and the extensions of the (Arc Map 9.3) program, which are (Spatial Analysis) And the three-dimensional analysis (3D analysis), and the outputs are the final process through which the results of the research emerge. These outputs show the type of information that will be processed and presented in the form of three-dimensional maps and shapes, studying the most important causes of geomorphological risks for the study area, and developing solutions and treatments through the conclusions and recommendations of the research.

scholarly journals Pemetaan Sebaran Daerah Asal Mahasiswa Universitas Negeri Manado Berbasis Sistem Informasi Geografis

2020 ◽  
Vol 1 (3) ◽  
pp. 1
Author(s):  
Nikel Tambengi ◽  
Joyce Christian Kumaat
Keyword(s):  
Information System ◽  
Spatial Distribution ◽  
Information Systems ◽  
Spatial Analysis ◽  
Geographical Information Systems ◽  
Geographic Location ◽  
Geographical Information ◽  
Distribution Data ◽  
Present Information ◽  
Area Of Origin

The need for information regarding the spatial distribution of the area of origin of students who are currently studying at the Manado State University (UNIMA) is very important because the information built can provide useful input for planning, development, or evaluation. So that the distribution of the areas of origin of students who are studying at UNIMA can be mapped properly, an information system based on Geographical Information Systems (GIS) can be built according to its geographic location. This study aims to create and present information about the spatial distribution of students from UNIMA through GIS. Quantitative type research methods with a spatial analysis approach (spatial analysis) using secondary data. Data analysis techniques through Geographical Information Systems (GIS) to create a digital map of the spatial distribution of student origin using OpenStreetMap and Quantum GIS Zanzibar 3.8.1. The results showed that the spatial distribution of the area from which UNIMA students used GIS, made it easier to present information through digital maps. The information system created can display the distribution data of the student's area of origin, namely the number of students from each province in Indonesia and especially in the form of a distribution map. The largest distribution of student origin came from North Sumatra Province with 1,209, followed by South Sulawesi Province with 893 and North Maluku Province with 650 students.

Geographical Information Systems and the Study of History

2011 ◽  
Vol 42 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Jordi Martí-Henneberg
Keyword(s):  
Information Systems ◽  
Spatial Analysis ◽  
Geographical Information Systems ◽  
Population Distribution ◽  
Historical Research ◽  
Transport Infrastructure ◽  
Geographical Information ◽  
Common Theme ◽  
Special Issue ◽  
Twentieth Century Europe

The articles in this special issue are unique in their use of historical geographical information systems (hgis) to explore a common theme—transport infrastructure and its effects on population distribution in nineteenth- and twentieth-century Europe. Collectively and individually, they demonstrate how to integrate spatial analysis into historical research and how to bring a historical dimension to geographical analyses.

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