Computational techniques have been adopted in medi-cal and biological systems for a long time. There is no doubt that the development and application of computational methods will render great help in better understan...Computational techniques have been adopted in medi-cal and biological systems for a long time. There is no doubt that the development and application of computational methods will render great help in better understanding biomedical and biological functions. Large amounts of datasets have been produced by biomedical and biological experiments and simulations. In order for researchers to gain knowledge from origi- nal data, nontrivial transformation is necessary, which is regarded as a critical link in the chain of knowledge acquisition, sharing, and reuse. Challenges that have been encountered include: how to efficiently and effectively represent human knowledge in formal computing models, how to take advantage of semantic text mining techniques rather than traditional syntactic text mining, and how to handle security issues during the knowledge sharing and reuse. This paper summarizes the state-of-the-art in these research directions. We aim to provide readers with an introduction of major computing themes to be applied to the medical and biological research.展开更多
A growing interest in producing and sharing computable biomedical knowledge artifacts(CBKs) is increasing the demand for repositories that validate, catalog, and provide shared access to CBKs. However, there is a lack...A growing interest in producing and sharing computable biomedical knowledge artifacts(CBKs) is increasing the demand for repositories that validate, catalog, and provide shared access to CBKs. However, there is a lack of evidence on how best to manage and sustain CBK repositories. In this paper, we present the results of interviews with several pioneering CBK repository owners. These interviews were informed by the Trusted Repositories Audit and Certification(TRAC) framework. Insights gained from these interviews suggest that the organizations operating CBK repositories are somewhat new, that their initial approaches to repository governance are informal, and that achieving economic sustainability for their CBK repositories is a major challenge. To enable a learning health system to make better use of its data intelligence, future approaches to CBK repository management will require enhanced governance and closer adherence to best practice frameworks to meet the needs of myriad biomedical science and health communities. More effort is needed to find sustainable funding models for accessible CBK artifact collections.展开更多
This article continued to do the scholastic pursuits on some profound mechanisms in the life systems, which are believed to be related to the further development of Medical Informatics. It discussed at first the struc...This article continued to do the scholastic pursuits on some profound mechanisms in the life systems, which are believed to be related to the further development of Medical Informatics. It discussed at first the structural nature of things, then probed a principle which is a basis for both of the fractal theory and the wavelet analysis, being called the shape-constancy law of the basic constructors at the different scale levels. And the paper also ventured the equivalency between the shape of wave and matrix, thus presented a new concept “shaped-number”, being expected to work in the operations of some bio-medical functions or shapes.展开更多
利用自然语言处理技术从生物医学文本中抽取药物治疗、疾病诊断等事件以及事件中涉及的疾病、药物等实体,对于生物医学领域相关学术研究以及各类生物医学应用系统具有重要意义。针对生物医学文本中的缩略词及专业术语难以识别和生物医...利用自然语言处理技术从生物医学文本中抽取药物治疗、疾病诊断等事件以及事件中涉及的疾病、药物等实体,对于生物医学领域相关学术研究以及各类生物医学应用系统具有重要意义。针对生物医学文本中的缩略词及专业术语难以识别和生物医学语义关系难以嵌入的问题,提出了一种融合外部知识和图卷积神经网络的生物医学信息联合识别模型。图卷积神经网络构建了包含实体和语义关系的异构图,能够迭代地融合本地知识图和外部知识图中的交互信息,根据得到的交互信息来进行生物医学实体对之间关系的抽取任务。预训练编码后利用图卷积神经网络构建本地和外部知识两个知识图,获得两个图中每个节点的特征表示,并且通过注意力实体链接的方法将两个图进行融合与信息迭代,进而抽取其最后一层隐藏层来完成最终的分类识别。其中统一医学语言系统(unified medical language system,UMLS)被用作实体消歧的外部知识库,实体链接器根据注意力权重选择对应实体。通过在MLEE语料库上进行的实验表明,联合任务能够实现事件抽取和触发词、元素识别的综合性能。展开更多
文摘Computational techniques have been adopted in medi-cal and biological systems for a long time. There is no doubt that the development and application of computational methods will render great help in better understanding biomedical and biological functions. Large amounts of datasets have been produced by biomedical and biological experiments and simulations. In order for researchers to gain knowledge from origi- nal data, nontrivial transformation is necessary, which is regarded as a critical link in the chain of knowledge acquisition, sharing, and reuse. Challenges that have been encountered include: how to efficiently and effectively represent human knowledge in formal computing models, how to take advantage of semantic text mining techniques rather than traditional syntactic text mining, and how to handle security issues during the knowledge sharing and reuse. This paper summarizes the state-of-the-art in these research directions. We aim to provide readers with an introduction of major computing themes to be applied to the medical and biological research.
基金supported by National Natural Science Foundation of China(71402157)the Natural Science Foundation of Guangdong Province,China(2014A030313753)+2 种基金CityU Start-up(7200399)the Center for Adaptive Super Computing Software-Multi Threaded Architectures(CASS-MT)at the U.S.Department of Energy’s Pacific Northwest National LaboratoryPacific Northwest National Laboratory Is Operated by Battelle Memorial Institute(Contract DE-ACO6-76RL01830)
文摘A growing interest in producing and sharing computable biomedical knowledge artifacts(CBKs) is increasing the demand for repositories that validate, catalog, and provide shared access to CBKs. However, there is a lack of evidence on how best to manage and sustain CBK repositories. In this paper, we present the results of interviews with several pioneering CBK repository owners. These interviews were informed by the Trusted Repositories Audit and Certification(TRAC) framework. Insights gained from these interviews suggest that the organizations operating CBK repositories are somewhat new, that their initial approaches to repository governance are informal, and that achieving economic sustainability for their CBK repositories is a major challenge. To enable a learning health system to make better use of its data intelligence, future approaches to CBK repository management will require enhanced governance and closer adherence to best practice frameworks to meet the needs of myriad biomedical science and health communities. More effort is needed to find sustainable funding models for accessible CBK artifact collections.
基金国家自然科学基金(31100592)国家高技术研究发展计划(863)(2012AA02A601+7 种基金2012AA02A6022012AA020201)国家科技重大专项(2013ZX03005012)supported by grants from The National Natural Science Foundation of China(31100592)National High Technology Research and Development Programs of China(863 Programs)(2012AA02A6012012AA02A6022012AA020201)National Science and Technology Major Project of China(2013ZX03005012)
文摘This article continued to do the scholastic pursuits on some profound mechanisms in the life systems, which are believed to be related to the further development of Medical Informatics. It discussed at first the structural nature of things, then probed a principle which is a basis for both of the fractal theory and the wavelet analysis, being called the shape-constancy law of the basic constructors at the different scale levels. And the paper also ventured the equivalency between the shape of wave and matrix, thus presented a new concept “shaped-number”, being expected to work in the operations of some bio-medical functions or shapes.
文摘利用自然语言处理技术从生物医学文本中抽取药物治疗、疾病诊断等事件以及事件中涉及的疾病、药物等实体,对于生物医学领域相关学术研究以及各类生物医学应用系统具有重要意义。针对生物医学文本中的缩略词及专业术语难以识别和生物医学语义关系难以嵌入的问题,提出了一种融合外部知识和图卷积神经网络的生物医学信息联合识别模型。图卷积神经网络构建了包含实体和语义关系的异构图,能够迭代地融合本地知识图和外部知识图中的交互信息,根据得到的交互信息来进行生物医学实体对之间关系的抽取任务。预训练编码后利用图卷积神经网络构建本地和外部知识两个知识图,获得两个图中每个节点的特征表示,并且通过注意力实体链接的方法将两个图进行融合与信息迭代,进而抽取其最后一层隐藏层来完成最终的分类识别。其中统一医学语言系统(unified medical language system,UMLS)被用作实体消歧的外部知识库,实体链接器根据注意力权重选择对应实体。通过在MLEE语料库上进行的实验表明,联合任务能够实现事件抽取和触发词、元素识别的综合性能。
