{"id":{"repo_id":"aachen","oai_identifier":"oai:publications.rwth-aachen.de:61710"},"canonical_url":"https://search.dev.ndltd.org/etd/aachen/oai:publications.rwth-aachen.de:61710","repository":{"repo_id":"aachen","name":"RWTH Aachen University","base_url":"https://publications.rwth-aachen.de/oai2d"},"display":{"title":"Anwendung eines objektorientierten Wissensmodells mit zugrunde liegendem semantischen Netz als Entscheidungsunterstützungs- und Lernsystem in der Medizin","abstract":"Medical knowledge is growing at a tremendous pace. Since its application is critical with respect to patients' health, a computer-based representation of this knowledge is becoming increasingly important. This work contributes to the development of Datamed, a knowledge-based system in medicine. Datamed can be used to support a physician's clinical decision process as well as to teach medical students. Datamed's knowledge is stored in a semantic network which consists of objects and associations. Objects represent medical concepts such as measels, fever, or the digestive system. Associations define relations between objects: abdomen and appendix, for example, can be linked by a \"part of\" relation. Thus, we can model statements such as \"Measels show the symptom of fever\" by two objects \"Measels\" and \"Fever\" and an association \"has symptom\" connecting them. Choosing pediatric viral infections as an example, we fill the semantic network by incorporating text book knowledge. Additionally, we include multimedia elements such as pictures and animations. To facilitate intelligent reasoning, we use the Systematized Nomenclature of Medicine, SNOMED. Currently, Datamed hosts 549 objects and 1041 associations. Besides contributing to the design of the knowledge base, this thesis focused on the development of a system that allows for an interaction with the stored knowledge. To this end, requirements of possible users were first identified. Using Persona Modelling, two fictitious characters were created and described in detail, subsuming goals, skills, previous knownledge as well as typical questions of typical users. The abstraction of this led to generic queries and functional requirements for the system. The graphical user interface was designed accordingly and implemented in HTML. Cognitive Walkthrough, a method for usability testing, was successfully employed to improve the interface. As a result, the Datamed's graphical interface offers a variety of views on the data. Especially interesting is the visualisation of the semantic network. It immediately shows how different symptoms are connected to different diseases: which symptoms are common to several dieases, and which symptoms are pathognomonic, i.e. are connected to only one disease. This fuels learning, as it simultaneously displays text book facts in a way that resembles the clinical reasoning process. In addition, the text book excerpt that was used to model the semantic network is included as well, and can serve to clarify and substantiate the presented knowledge. Regarding sustainability, we show that Datamed is a framework which is easily adaptable, scalable, and extensible. Recently, curricula in medical student education set out to incorporate new methodologies such as problem-oriented learning, E-learning, or virtual education. Datamed's crosslinking of concepts accounts for interdisciplinary learning that complements traditional approaches. In addition, exploring the semantic network is fun, thus making learning with it more efficient. We conclude that Datamed can contribute to improving the education of medical students as well as preparing for the challenges in the clinical decision process of physicians.","abstract_html":"Medical knowledge is growing at a tremendous pace. Since its application is critical with respect to patients' health, a computer-based representation of this knowledge is becoming increasingly important. This work contributes to the development of Datamed, a knowledge-based system in medicine. Datamed can be used to support a physician's clinical decision process as well as to teach medical students. Datamed's knowledge is stored in a semantic network which consists of objects and associations. Objects represent medical concepts such as measels, fever, or the digestive system. Associations define relations between objects: abdomen and appendix, for example, can be linked by a "part of" relation. Thus, we can model statements such as "Measels show the symptom of fever" by two objects "Measels" and "Fever" and an association "has symptom" connecting them. Choosing pediatric viral infections as an example, we fill the semantic network by incorporating text book knowledge. Additionally, we include multimedia elements such as pictures and animations. To facilitate intelligent reasoning, we use the Systematized Nomenclature of Medicine, SNOMED. Currently, Datamed hosts 549 objects and 1041 associations. Besides contributing to the design of the knowledge base, this thesis focused on the development of a system that allows for an interaction with the stored knowledge. To this end, requirements of possible users were first identified. Using Persona Modelling, two fictitious characters were created and described in detail, subsuming goals, skills, previous knownledge as well as typical questions of typical users. The abstraction of this led to generic queries and functional requirements for the system. The graphical user interface was designed accordingly and implemented in HTML. Cognitive Walkthrough, a method for usability testing, was successfully employed to improve the interface. As a result, the Datamed's graphical interface offers a variety of views on the data. Especially interesting is the visualisation of the semantic network. It immediately shows how different symptoms are connected to different diseases: which symptoms are common to several dieases, and which symptoms are pathognomonic, i.e. are connected to only one disease. This fuels learning, as it simultaneously displays text book facts in a way that resembles the clinical reasoning process. In addition, the text book excerpt that was used to model the semantic network is included as well, and can serve to clarify and substantiate the presented knowledge. Regarding sustainability, we show that Datamed is a framework which is easily adaptable, scalable, and extensible. Recently, curricula in medical student education set out to incorporate new methodologies such as problem-oriented learning, E-learning, or virtual education. Datamed's crosslinking of concepts accounts for interdisciplinary learning that complements traditional approaches. In addition, exploring the semantic network is fun, thus making learning with it more efficient. 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Since its application is critical with respect to patients' health, a computer-based representation of this knowledge is becoming increasingly important. This work contributes to the development of Datamed, a knowledge-based system in medicine. Datamed can be used to support a physician's clinical decision process as well as to teach medical students. Datamed's knowledge is stored in a semantic network which consists of objects and associations. Objects represent medical concepts such as measels, fever, or the digestive system. Associations define relations between objects: abdomen and appendix, for example, can be linked by a \"part of\" relation. Thus, we can model statements such as \"Measels show the symptom of fever\" by two objects \"Measels\" and \"Fever\" and an association \"has symptom\" connecting them. Choosing pediatric viral infections as an example, we fill the semantic network by incorporating text book knowledge. Additionally, we include multimedia elements such as pictures and animations. To facilitate intelligent reasoning, we use the Systematized Nomenclature of Medicine, SNOMED. Currently, Datamed hosts 549 objects and 1041 associations. Besides contributing to the design of the knowledge base, this thesis focused on the development of a system that allows for an interaction with the stored knowledge. To this end, requirements of possible users were first identified. Using Persona Modelling, two fictitious characters were created and described in detail, subsuming goals, skills, previous knownledge as well as typical questions of typical users. The abstraction of this led to generic queries and functional requirements for the system. The graphical user interface was designed accordingly and implemented in HTML. Cognitive Walkthrough, a method for usability testing, was successfully employed to improve the interface. As a result, the Datamed's graphical interface offers a variety of views on the data. Especially interesting is the visualisation of the semantic network. It immediately shows how different symptoms are connected to different diseases: which symptoms are common to several dieases, and which symptoms are pathognomonic, i.e. are connected to only one disease. This fuels learning, as it simultaneously displays text book facts in a way that resembles the clinical reasoning process. In addition, the text book excerpt that was used to model the semantic network is included as well, and can serve to clarify and substantiate the presented knowledge. Regarding sustainability, we show that Datamed is a framework which is easily adaptable, scalable, and extensible. Recently, curricula in medical student education set out to incorporate new methodologies such as problem-oriented learning, E-learning, or virtual education. 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Additionally, we include multimedia elements such as pictures and animations. To facilitate intelligent reasoning, we use the Systematized Nomenclature of Medicine, SNOMED. Currently, Datamed hosts 549 objects and 1041 associations. Besides contributing to the design of the knowledge base, this thesis focused on the development of a system that allows for an interaction with the stored knowledge. To this end, requirements of possible users were first identified. Using Persona Modelling, two fictitious characters were created and described in detail, subsuming goals, skills, previous knownledge as well as typical questions of typical users. The abstraction of this led to generic queries and functional requirements for the system. The graphical user interface was designed accordingly and implemented in HTML. Cognitive Walkthrough, a method for usability testing, was successfully employed to improve the interface. As a result, the Datamed's graphical interface offers a variety of views on the data. Especially interesting is the visualisation of the semantic network. It immediately shows how different symptoms are connected to different diseases: which symptoms are common to several dieases, and which symptoms are pathognomonic, i.e. are connected to only one disease. This fuels learning, as it simultaneously displays text book facts in a way that resembles the clinical reasoning process. In addition, the text book excerpt that was used to model the semantic network is included as well, and can serve to clarify and substantiate the presented knowledge. Regarding sustainability, we show that Datamed is a framework which is easily adaptable, scalable, and extensible. Recently, curricula in medical student education set out to incorporate new methodologies such as problem-oriented learning, E-learning, or virtual education. Datamed's crosslinking of concepts accounts for interdisciplinary learning that complements traditional approaches. In addition, exploring the semantic network is fun, thus making learning with it more efficient. We conclude that Datamed can contribute to improving the education of medical students as well as preparing for the challenges in the clinical decision process of physicians."],"dc:identifier":["https://publications.rwth-aachen.de/record/61710","https://publications.rwth-aachen.de/search?p=id:%22RWTH-CONV-123345%22"],"dc:language":["ger"],"dc:publisher":["Publikationsserver der RWTH Aachen University"],"dc:relation":["info:eu-repo/semantics/altIdentifier/urn/urn:nbn:de:hbz:82-opus-18222"],"dc:rights":["info:eu-repo/semantics/openAccess"],"dc:source":["Aachen : Publikationsserver der RWTH Aachen University III, 121 S. : Ill., graph. Darst. (2007). = Aachen, Techn. 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