This article identifies the role of library and information science (LIS) education in the development of community health information services for people living with HIV/AIDS (PLWHA). Preliminary findings are present...This article identifies the role of library and information science (LIS) education in the development of community health information services for people living with HIV/AIDS (PLWHA). Preliminary findings are presented from semi- structured qualitative interviews that were conducted with eleven directors and managers of local branches in the Knox County Public Library (KCPL) System that is located in the East Tennessee region in the United States. Select feedback reported by research participants is summarized in the article about strategies in LIS education that can help local public librarians and others in their efforts to become more responsive information providers to PLWHA. Research findings help better understand the issues and concerns regarding the development of digital and non-digital health information services for PLWHA in local public library institutions.展开更多
Background: The fatality of adverse drug reactions (ADR) has become one of the major causes of the non-natural disease deaths globally, with the issue of drug safety emerging as a common topic of concern. Objective: T...Background: The fatality of adverse drug reactions (ADR) has become one of the major causes of the non-natural disease deaths globally, with the issue of drug safety emerging as a common topic of concern. Objective: The personalized ADR early warning method, based on contextual ontology and rule learning, proposed in this study aims to provide a reference method for personalized health and medical information services. Methods: First, the patient data is formalized, and the user contextual ontology is constructed, reflecting the characteristics of the patient population. The concept of ontology rule learning is then proposed, which is to mine the rules contained in the data set through machine learning to improve the efficiency and scientificity of ontology rule generation. Based on the contextual ontology of ADR, the high-level context information is identified and predicted by means of reasoning, so the occurrence of the specific adverse reaction in patients from different populations is extracted. Results: Finally, using diabetes drugs as an example, contextual information is identified and predicted through reasoning, to mine the occurrence of specific adverse reactions in different patient populations, and realize personalized medication decision-making and early warning of ADR.展开更多
文摘This article identifies the role of library and information science (LIS) education in the development of community health information services for people living with HIV/AIDS (PLWHA). Preliminary findings are presented from semi- structured qualitative interviews that were conducted with eleven directors and managers of local branches in the Knox County Public Library (KCPL) System that is located in the East Tennessee region in the United States. Select feedback reported by research participants is summarized in the article about strategies in LIS education that can help local public librarians and others in their efforts to become more responsive information providers to PLWHA. Research findings help better understand the issues and concerns regarding the development of digital and non-digital health information services for PLWHA in local public library institutions.
文摘Background: The fatality of adverse drug reactions (ADR) has become one of the major causes of the non-natural disease deaths globally, with the issue of drug safety emerging as a common topic of concern. Objective: The personalized ADR early warning method, based on contextual ontology and rule learning, proposed in this study aims to provide a reference method for personalized health and medical information services. Methods: First, the patient data is formalized, and the user contextual ontology is constructed, reflecting the characteristics of the patient population. The concept of ontology rule learning is then proposed, which is to mine the rules contained in the data set through machine learning to improve the efficiency and scientificity of ontology rule generation. Based on the contextual ontology of ADR, the high-level context information is identified and predicted by means of reasoning, so the occurrence of the specific adverse reaction in patients from different populations is extracted. Results: Finally, using diabetes drugs as an example, contextual information is identified and predicted through reasoning, to mine the occurrence of specific adverse reactions in different patient populations, and realize personalized medication decision-making and early warning of ADR.
