Alzheimer’s disease(AD)is a very complex disease that causes brain failure,then eventually,dementia ensues.It is a global health problem.99%of clinical trials have failed to limit the progression of this disease.The ...Alzheimer’s disease(AD)is a very complex disease that causes brain failure,then eventually,dementia ensues.It is a global health problem.99%of clinical trials have failed to limit the progression of this disease.The risks and barriers to detecting AD are huge as pathological events begin decades before appearing clinical symptoms.Therapies for AD are likely to be more helpful if the diagnosis is determined early before the final stage of neurological dysfunction.In this regard,the need becomes more urgent for biomarker-based detection.A key issue in understanding AD is the need to solve complex and high-dimensional datasets and heterogeneous biomarkers,such as genetics,magnetic resonance imaging(MRI),cerebrospinal fluid(CSF),and cognitive scores.Establishing an interpretable reasoning system and performing interoperability that achieves in terms of a semantic model is potentially very useful.Thus,our aim in this work is to propose an interpretable approach to detect AD based on Alzheimer’s disease diagnosis ontology(ADDO)and the expression of semantic web rule language(SWRL).This work implements an ontology-based application that exploits three different machine learning models.These models are random forest(RF),JRip,and J48,which have been used along with the voting ensemble.ADNI dataset was used for this study.The proposed classifier’s result with the voting ensemble achieves a higher accuracy of 94.1%and precision of 94.3%.Our approach provides effective inference rules.Besides,it contributes to a real,accurate,and interpretable classifier model based on various AD biomarkers for inferring whether the subject is a normal cognitive(NC),significant memory concern(SMC),early mild cognitive impairment(EMCI),late mild cognitive impairment(LMCI),or AD.展开更多
Modem product development becomes increasingly collaborative and integrated, which raises the need for effectively and efficiently sharing and re-using design knowledge in a distributed and collaborative environment. ...Modem product development becomes increasingly collaborative and integrated, which raises the need for effectively and efficiently sharing and re-using design knowledge in a distributed and collaborative environment. To address this need, a framework is developed in this research to support design knowledge representation, retrieval, reasoning and fusion, which takes account of structural, functional and behavioral data, various design attributes and knowledge reasoning cases. Specifically, a multi-level knowledge representation based on the Base Object Model （BOM） is proposed to enable knowledge sharing using Web services technologies. On this basis, a multi-level knowledge reuse method is developed to support the retrieval, matching and assembly of knowledge records. Due to the tree structure of BOM, both depth-first and breadth-first searching strategies are employed in the retrieval algorithm while a novel measure is proposed to evaluate similarity. Moreover, a method based on the D-S evidence theory is developed to enable knowledge fusion and thus support effective decision-making. The framework has been implemented and integrated into an HLA-based simulation platform on which the development of a missile simulation example is conducted. It is demonstrated in the case study that the proposed framework and methods are useful and effective for design knowledge representation and reuse.展开更多
以国际核心期刊Research Policy(《科研政策》)2007—2017年发表的文献为研究对象,借助VOSviewer和Cite Space II软件分别制作文献有关社会网络、共现网络等知识图谱,对国际科技政策研究状况进行可视化分析。研究表明:(1)欧美发达国家...以国际核心期刊Research Policy(《科研政策》)2007—2017年发表的文献为研究对象,借助VOSviewer和Cite Space II软件分别制作文献有关社会网络、共现网络等知识图谱,对国际科技政策研究状况进行可视化分析。研究表明:(1)欧美发达国家引领了科技政策研究前沿,但国家的发文数量和影响力之间无明显线性比例关系,跨国合作态势明显;(2)国际科技政策研究基础主要集中在社会技术创新范式等6大领域;(3)创新政策是国际科技政策的主旋律,企业开放式创新等6个方面是国际科技政策研究的热点领域,其中我国更加关注研发政策;(4)科技政策演进先后经历了4个阶段,从国家创新系统为主导到技术创新与转移为主导,从产业发展实证研究为主导到研发补贴等研究多元化发展。展开更多
基金This work was supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.2021R1A2C1011198).
文摘Alzheimer’s disease(AD)is a very complex disease that causes brain failure,then eventually,dementia ensues.It is a global health problem.99%of clinical trials have failed to limit the progression of this disease.The risks and barriers to detecting AD are huge as pathological events begin decades before appearing clinical symptoms.Therapies for AD are likely to be more helpful if the diagnosis is determined early before the final stage of neurological dysfunction.In this regard,the need becomes more urgent for biomarker-based detection.A key issue in understanding AD is the need to solve complex and high-dimensional datasets and heterogeneous biomarkers,such as genetics,magnetic resonance imaging(MRI),cerebrospinal fluid(CSF),and cognitive scores.Establishing an interpretable reasoning system and performing interoperability that achieves in terms of a semantic model is potentially very useful.Thus,our aim in this work is to propose an interpretable approach to detect AD based on Alzheimer’s disease diagnosis ontology(ADDO)and the expression of semantic web rule language(SWRL).This work implements an ontology-based application that exploits three different machine learning models.These models are random forest(RF),JRip,and J48,which have been used along with the voting ensemble.ADNI dataset was used for this study.The proposed classifier’s result with the voting ensemble achieves a higher accuracy of 94.1%and precision of 94.3%.Our approach provides effective inference rules.Besides,it contributes to a real,accurate,and interpretable classifier model based on various AD biomarkers for inferring whether the subject is a normal cognitive(NC),significant memory concern(SMC),early mild cognitive impairment(EMCI),late mild cognitive impairment(LMCI),or AD.
基金This research is supported by the National Natural Science Foundation of China （Grant No.61374163）, the National Key Technology R＆D Program （Grant No. 2012BAF15G00）, the National High Technology Research and Development Program （863 Program） of China （Grant No.2013AA041302）. Acknowledgments This research is supported by the National Natural Science Foundation of China （Grant No.61374163 ） , the National Key Technology R＆D Program （Grant No. 2012BAF 15G00）, the National High Technology Research and Development Program （863 Program） of China （Grant No.2013AA041302）. The original version of this paper was presented at the 18th 1EEE CSCWD Conference held in Taiwan, China in May 2014.
文摘Modem product development becomes increasingly collaborative and integrated, which raises the need for effectively and efficiently sharing and re-using design knowledge in a distributed and collaborative environment. To address this need, a framework is developed in this research to support design knowledge representation, retrieval, reasoning and fusion, which takes account of structural, functional and behavioral data, various design attributes and knowledge reasoning cases. Specifically, a multi-level knowledge representation based on the Base Object Model （BOM） is proposed to enable knowledge sharing using Web services technologies. On this basis, a multi-level knowledge reuse method is developed to support the retrieval, matching and assembly of knowledge records. Due to the tree structure of BOM, both depth-first and breadth-first searching strategies are employed in the retrieval algorithm while a novel measure is proposed to evaluate similarity. Moreover, a method based on the D-S evidence theory is developed to enable knowledge fusion and thus support effective decision-making. The framework has been implemented and integrated into an HLA-based simulation platform on which the development of a missile simulation example is conducted. It is demonstrated in the case study that the proposed framework and methods are useful and effective for design knowledge representation and reuse.
文摘以国际核心期刊Research Policy(《科研政策》)2007—2017年发表的文献为研究对象,借助VOSviewer和Cite Space II软件分别制作文献有关社会网络、共现网络等知识图谱,对国际科技政策研究状况进行可视化分析。研究表明:(1)欧美发达国家引领了科技政策研究前沿,但国家的发文数量和影响力之间无明显线性比例关系,跨国合作态势明显;(2)国际科技政策研究基础主要集中在社会技术创新范式等6大领域;(3)创新政策是国际科技政策的主旋律,企业开放式创新等6个方面是国际科技政策研究的热点领域,其中我国更加关注研发政策;(4)科技政策演进先后经历了4个阶段,从国家创新系统为主导到技术创新与转移为主导,从产业发展实证研究为主导到研发补贴等研究多元化发展。
