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| 2. |
- Andersson, Birger, et al.
(författare)
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Towards a Common Business Ontology
- 2006
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Ingår i: Proceedings of the 3rd Open Interop Workshop on Enterprise Modelling and Ontologies for Interoperability (Interop-EMOI'06). - Luxembourg.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)
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| 3. |
- Andersson, Birger, et al.
(författare)
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Towards a common ontology for a business domain : Issues and possible solutions
- 2006
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Ingår i: Proceedings of the Open Interop Workshop onEnterprise Modelling and Ontologies for Interoperability. - : CEUR-WS.org.
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Konferensbidrag (refereegranskat)abstract
- To create an understanding of enterprises and the ways they do business, a starting point could be to identify the main actors and the values transferred between them. Business models are created in order to make clear who the business actors are in a business case and to make their relations explicit. The relations are formulated in terms of values exchanged between the actors. The purpose of the work reported in this paper is to create a better understanding of business models by identifying basic notions used in such models. It does so by constructing a common ontology based on three established business model ontologies: e3-value, REA, and BMO. By means of a careful analysis of these ontologies a conceptual schema is created that defines the common concepts. An example is worked out that explains how the common ontology should be understood.
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| 4. |
- Andersson, Birger, et al.
(författare)
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Towards a reference ontology for business models
- 2006
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Ingår i: Conceptual Modeling - ER 2006, Proceedings. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 354047224X ; , s. 482-496, s. 482-496
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Konferensbidrag (refereegranskat)abstract
- Ontologies are viewed as increasingly important tools for structuring domains of interests. In this paper we propose a reference ontology of business models using concepts from three established business model ontologies; the REA, BMO, and e3-value. The basic concepts in the reference ontology concern actors, resources, and the transfer of resources between actors. Most of the concepts in the reference ontology are taken from one of the original ontologies, but we have also introduced a number of additional concepts, primarily related to resource transfers between business actors. The purpose of the proposed ontology is to increase the understanding of the original ontologies as well as the relationships between them, and also to seek opportunities to complement and improve on them.
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| 5. |
- Andersson, Birger, et al.
(författare)
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Towards a Reference Ontology for Business Models
- 2006
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Ingår i: Proceedings of the 25th International Conference on Conceptual Modeling (ER 2006). - Tucson, AZ, USA.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)
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| 6. |
- Unkelbach, Jan, et al.
(författare)
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The role of computational methods for automating and improving clinical target volume definition
- 2020
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Ingår i: Radiotherapy and Oncology. - : Elsevier BV. - 0167-8140 .- 1879-0887. ; 153, s. 15-25
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Tidskriftsartikel (refereegranskat)abstract
- Treatment planning in radiotherapy distinguishes three target volume concepts: the gross tumor volume(GTV), the clinical target volume (CTV), and the planning target volume (PTV). Over time, GTV definitionand PTV margins have improved through the development of novel imaging techniques and better imageguidance, respectively. CTV definition is sometimes considered the weakest element in the planning pro-cess. CTV definition is particularly complex since the extension of microscopic disease cannot be seenusing currently available in-vivo imaging techniques. Instead, CTV definition has to incorporate knowl-edge of the patterns of tumor progression. While CTV delineation has largely been considered the domainof radiation oncologists, this paper, arising from a 2019 ESTRO Physics research workshop, discusses thecontributions that medical physics and computer science can make by developing computational meth-ods to support CTV definition. First, we overview the role of image segmentation algorithms, which mayin part automate CTV delineation through segmentation of lymph node stations or normal tissues repre-senting anatomical boundaries of microscopic tumor progression. The recent success of deep convolu-tional neural networks has also enabled learning entire CTV delineations from examples. Second, wediscuss the use of mathematical models of tumor progression for CTV definition, using as example theapplication of glioma growth models to facilitate GTV-to-CTV expansion for glioblastoma that is consis-tent with neuroanatomy. We further consider statistical machine learning models to quantify lymphaticmetastatic progression of tumors, which may eventually improve elective CTV definition. Lastly, we dis-cuss approaches to incorporate uncertainty in CTV definition into treatment plan optimization as well asgeneral limitations of the CTV concept in the case of infiltrating tumors without natural boundaries.
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