Biomedical knowledge bases

The Unified Medical Language System (UMLS) integrates various source terminologies to support interoperability between biomedical information systems. In this article, we introduce a novel transformationbased auditing method that leverages the UMLS knowledge to systematically identify missing hierarchical IS-A relations in the source terminologies.

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Semantic similarity measures estimate the similarity between concepts, and play an important role in many text processing tasks. Approaches to semantic similarity in the biomedical domain can be roughly divided into knowledge based and distributional based methods.

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Graph-based notions are increasingly used in biomedical data mining and knowledge discovery tasks. In this paper, we present a clique-clustering method to automatically summarize graphs of semantic predications produced from PubMed citations (titles and abstracts).

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Many biomedical relation extraction systems are machine-learning based and have to be trained on large annotated corpora that are expensive and cumbersome to construct. We developed a knowledge-based relation extraction system that requires minimal training data, and applied the system for the extraction of adverse drug events from biomedical text.

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Biomedical knowledge bases (KB’s) have become important assets in life sciences. Prior work on KB construction has three major limitations. First, most biomedical KBs are manually built and curated, and cannot keep up with the rate at which new findings are published;...

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The ability to query many independent biological databases using a common ontology-based semantic model would facilitate deeper integration and more effective utilization of these diverse and rapidly growing resources. Despite ongoing work moving toward shared data formats and linked identifiers, significant problems persist in semantic data integration in order to establish shared identity and shared meaning across heterogeneous biomedical data sources.

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Literature based discovery (LBD) automatically infers missed connections between concepts in literature. It is often assumed that LBD generates more information than can be reasonably examined.

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Biomedical knowledge grows in complexity, and becomes encoded in network-based repositories, which include focused, expert-drawn diagrams, networks of evidence-based associations and established ontologies.

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Automatic extraction of chemical-disease relations (CDR) from unstructured text is of essential importance for disease treatment and drug development. Meanwhile, biomedical experts have built many highlystructured knowledge bases (KBs), which contain prior knowledge about chemicals and diseases. Prior knowledge provides strong support for CDR extraction. How to make full use of it is worth studying.

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In recent years, biomedical ontologies have become important for describing existing biological knowledge in the form of knowledge graphs. Data mining approaches that work with knowledge graphs have been proposed, but they are based on vector representations that do not capture the full underlying semantics. An alternative is to use machine learning approaches that explore semantic similarity.

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Automated biomedical named entity recognition and normalization serves as the basis for many downstream applications in information management. However, this task is challenging due to name variations and entity ambiguity. A biomedical entity may have multiple variants and a variant could denote several different entity identifiers.

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Biomedical waste (BMW) is generated in every health facility, which if not disposed off properly poses a risk for health and environment. Handling, segregation, mutilation, disinfection, storage, transportation and final disposal are vital steps for safe and scientific management of biomedical waste in any establishment. The objective was to assess the biomedical waste management (BMWM) practices and knowledge regarding BMWM in a tertiary care hospital.

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The present study systematically reviewed research articles published in international academic journals from 2007 to 2016, analyzed the application domains, subjects, and adopted learning strategies, and investigated the research issues of smartphone-supported medical education. The findings revealed that the application of smartphones in medical education and training has not gained much popularity over the past years.

20p kequaidan1 05-11-2019 33 2   Download

Fault diagnosis is a complex and fuzzy cognitive process, and soft computing methods as neural networks and fuzzy logic, have shown great potential in the development of decision support systems. Dealing with expert (human) knowledge consideration, Computer-Aided Diagnosis (CAD) dilemma is one of the most interesting, but also one of the most difficult problems.

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Pressing demand. Past market-based systems never saw real field testing, and contention was often artifi- cially generated. Today, a deployed market system could have immediate usage and solve real resource conflicts. Real usage data will help researchers calibrate and eval- uate their market-based resource schedulers. Previous mechanism designs were not able to take advantage of user feedback to drive the mechanism design process. Improved operating system infrastructure.

5p nhacsihuytuan 06-04-2013 58 6   Download

This report focuses on a set of tools to address youth exposure that has been largely ignored: State laws that restrict youth expo- sure to alcohol advertising in both measured and unmeasured media venues. States have systems already in place for administer- ing alcohol advertising regulations, usually (but not always) housed in an Alcoholic Beverage Control (ABC) state agency. Alcohol producers, distributors, and retailers must obtain state licenses to do business in a state.

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For many marketers, mobile is the Holy Grail for Location Based Marketing. Location Based Marketing promises an unprecedented new way to connect with consumers and deliver highly relevant and targeted messages at a time and place when a consumer is most likely to act on them. The Mobile Marketing Association (MMA) has developed this whitepaper to educate the industry on Location Based Marketing, and to provide a general overview for mobile marketers seeking to understand the potential opportunities for Location Based Services1 (“LBS).

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With Ministries of Health taking the lead, it is important for cervical cancer programmes to engage all levels of the health system while involving all non-health and private sector stakeholders as much as possible. This should take into consideration current health system structures, human resource capacity, funding mechanisms, health information systems, and access to health services. Decision-making at all levels should be evidence-based.

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established in the earliest history of the planet or as the result of a continuing supply of water and the constituents of sea water by degassing from the Earth’s interior. In 1951 W.W. Rubey, in his Presidential Address to the Geological Society of America, took the latter point of view. His arguments were colored by the knowledge available at that time of the age of the Earth and the age of the oldest rocks. Based on the analysis of lead isotopes in galenas, it was determined in the late 1940s that the Earth was about 3.2 billion years old.

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Based on your answers, good teachers are able to make a reliable estimate of the number of words you must transfer into your brain. This number varies between 5,000 and 15,000. Worst-case scenarios are languages that are completely different from any of the languages you know: for Europeans, typical examples are Hindi, Arabic, or Chinese. In these languages, only a handful of words resemble European words and leave you with 15,000 words on the table.

121p quynho77 12-11-2012 52 1   Download