Uniqueness of Group Decision Support Systems (GDSS) in medical and health applications
Journal of Medical Systems, ISSN: 0148-5598, Vol: 14, Issue: 6, Page: 351-364
1990
- 7Citations
- 16Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Metrics Details
- Citations7
- Citation Indexes7
- CrossRef4
- Academic Citation Index (ACI) - airiti1
- Captures16
- Readers16
- 16
Article Description
Group Decision Support Systems (GDSS) are defined and discussed. A GDSS model developed by the author is reviewed in depth for communication of the concepts of GDSS. The model's components are related to health care applications. Questions about unique requirements and level of sophistication in health care applications are explored. What are the differences? What is needed in GDSS software? How do implementation strategies differ? The purpose of this paper is to define and discuss the uniqueness and level of sophistication of GDSS applications in health care. The information requirements and level of information abstraction are the major forces considered in the design of specific medical GDSSs. Data for the GDSS and queries originate both internally and externally to the system. Raw data may be in image form and require extensive analysis by the decision makers for information to be extracted from the raw data. Efforts also are made to relate financial and medical data for better business decisions. This integration often has limited success. Additionally, financial data represent multiple sources and present concerns of validity and reliability. In medical diagnoses the knowledge bases are large and contain thousands of rules. Treatment planning and progress reporting rely on medical records that contain thousands of information items and that often require interpretation by an expert. These information attributes go beyond qualitative versus quantitative definitions and are the author's basis for the analysis presented in this paper. © 1990 Plenum Publishing Corporation.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=0025622460&origin=inward; http://dx.doi.org/10.1007/bf00996715; http://www.ncbi.nlm.nih.gov/pubmed/2132042; http://link.springer.com/10.1007/BF00996715; http://www.springerlink.com/index/pdf/10.1007/BF00996715; http://www.springerlink.com/index/10.1007/BF00996715; https://dx.doi.org/10.1007/bf00996715; https://link.springer.com/article/10.1007/BF00996715
Springer Science and Business Media LLC
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