ControlSem – distributed decision support system based on semantic web technologies for the analysis of the medical procedures

Andreasik, Jan; Ciebiera, Andrzej; Umpirowicz, Slawomir

doi:10.1109/hsi.2010.5742783

Cited by 2 publications

(2 citation statements)

References 6 publications

(5 reference statements)

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“…The system generates the knowledge about cases of non-compliance in prescribing drugs by doctors of specific health care institutions . I presented two papers at two international conferences (Andreasik, Ciebiera, andUmpirowicz 2010, 2011) .…”

Section: Design Of a System For Semantic Analysis Of Nhf Databasesmentioning

confidence: 99%

Knowledge Management Models. State of the Art

Andreasik¹

2019

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In this article knowledge management models are classified into the following groups: 1. Resource models. 1.1. Holistic models. 1.2. Pyramidal models. 2.Process models. 2.1. Knowledge value chain models. 2.2. Branch models of organizational processes. 2.3. Spiral models. 3. Knowledge creation models. 4. Semantic models. As the summary the operationalization of knowledge management models is presented.

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Section: Design Of a System For Semantic Analysis Of Nhf Databasesmentioning

confidence: 99%

Knowledge Management Models. State of the Art

Andreasik¹

2019

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“…In [14], a Semantic Web based Clinical Decision Support System is presented to provide evidence-guided recommendations for follow-up after treatment for Breast Cancer. ControlSem [15], a medical decision support system using Semantic Web technologies, was developed with the goal of controlling medical procedures. Similarly, in [16], the authors present a medical expert system for heart failure.…”

Section: Related Workmentioning

confidence: 99%

DC Proposal: Decision Support Methods in Community-Driven Knowledge Curation Platforms

Paul

2011

The Semantic Web – ISWC 2011

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Abstract. Skeletal dysplasias comprise a group of genetic diseases characterized by highly complex, heterogeneous and sparse data. Performing efficient and automated knowledge discovery in this domain poses serious challenges, one of the main issues being the lack of a proper formalization. Semantic Web technologies can, however, provide the appropriate means for encoding the knowledge and hence enabling complex forms of reasoning. We aim to develop decision support methods in the skeletal dysplasia domain by applying uncertainty reasoning over Semantic Web data. More specifically, we devise techniques for semi-automated diagnosis and key disease feature inferencing from an existing pool of patient cases -that are shared and discussed in the SKELETOME community-driven knowledge curation platform. The outcome of our research will enable clinicians and researchers to acquire a critical mass of structured knowledge that will sustain a better understanding of these genetic diseases and foster advances in the field.

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ControlSem – distributed decision support system based on semantic web technologies for the analysis of the medical procedures

Cited by 2 publications

References 6 publications

Knowledge Management Models. State of the Art

Knowledge Management Models. State of the Art

DC Proposal: Decision Support Methods in Community-Driven Knowledge Curation Platforms

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