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Results for “Terminology as Topic”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

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At least 703 records · Page 39Linked to original sources
PubMed2006

2005 American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.) Standards and Guidelines survey.

An online survey about the use and format of the American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.) Standards and Guidelines documents was conducted. The survey was sent to A.S.P.E.N. members, and an acceptable number of responses were received (470, or 9% of those surveyed). Most respondents indicated an overall satisfaction with the standards and guidelines and suggested format changes, many of which will be incorporated into future guidelines and standards. The results of this survey are presented here for general interest. Changes in the process with which A.S.P.E.N. produces standards and guidelines are discussed.

Humans↗
PubMed2005

Developmental screening.

An estimated 5 to 10% of the pediatric population has a developmental disability. The current strategy to identify these children is through developmental surveillance, a continuous procedure in which the health professional observes the infant, takes a developmental history, and elicits any concerns that the caregiver might have. However, identification of delayed children is ineffective when based solely on routine surveillance. A necessary adjunct is developmental screening: the process of systematically identifying children with suspected delay who need further assessment. Screening tests greatly improve the rate of identification. With the advent of intervention programs and the support of organizations such as the American Academy of Pediatrics, the topic of developmental screening is a timely and essential one. This review aims to describe the properties of screening tests, to evaluate the available tools for developmental screening while providing a representative sample of the currently available developmental tests, and, finally, to evaluate the efficacy of intervention programs, a needed prerequisite to justify screening.

Adolescent↗
PubMed2005

Learning statistical models for annotating proteins with function information using biomedical text.

BACKGROUND: The BioCreative text mining evaluation investigated the application of text mining methods to the task of automatically extracting information from text in biomedical research articles. We participated in Task 2 of the evaluation. For this task, we built a system to automatically annotate a given protein with codes from the Gene Ontology (GO) using the text of an article from the biomedical literature as evidence. METHODS: Our system relies on simple statistical analyses of the full text article provided. We learn n-gram models for each GO code using statistical methods and use these models to hypothesize annotations. We also learn a set of Naïve Bayes models that identify textual clues of possible connections between the given protein and a hypothesized annotation. These models are used to filter and rank the predictions of the n-gram models. RESULTS: We report experiments evaluating the utility of various components of our system on a set of data held out during development, and experiments evaluating the utility of external data sources that we used to learn our models. Finally, we report our evaluation results from the BioCreative organizers. CONCLUSION: We observe that, on the test data, our system performs quite well relative to the other systems submitted to the evaluation. From other experiments on the held-out data, we observe that (i) the Naïve Bayes models were effective in filtering and ranking the initially hypothesized annotations, and (ii) our learned models were significantly more accurate when external data sources were used during learning.

Bayes Theorem↗
PubMed2005

Mining protein function from text using term-based support vector machines.

BACKGROUND: Text mining has spurred huge interest in the domain of biology. The goal of the BioCreAtIvE exercise was to evaluate the performance of current text mining systems. We participated in Task 2, which addressed assigning Gene Ontology terms to human proteins and selecting relevant evidence from full-text documents. We approached it as a modified form of the document classification task. We used a supervised machine-learning approach (based on support vector machines) to assign protein function and select passages that support the assignments. As classification features, we used a protein's co-occurring terms that were automatically extracted from documents. RESULTS: The results evaluated by curators were modest, and quite variable for different problems: in many cases we have relatively good assignment of GO terms to proteins, but the selected supporting text was typically non-relevant (precision spanning from 3% to 50%). The method appears to work best when a substantial set of relevant documents is obtained, while it works poorly on single documents and/or short passages. The initial results suggest that our approach can also mine annotations from text even when an explicit statement relating a protein to a GO term is absent. CONCLUSION: A machine learning approach to mining protein function predictions from text can yield good performance only if sufficient training data is available, and significant amount of supporting data is used for prediction. The most promising results are for combined document retrieval and GO term assignment, which calls for the integration of methods developed in BioCreAtIvE Task 1 and Task 2.

Computational Biology↗
PubMed2006

Identifying biological concepts from a protein-related corpus with a probabilistic topic model.

BACKGROUND: Biomedical literature, e.g., MEDLINE, contains a wealth of knowledge regarding functions of proteins. Major recurring biological concepts within such text corpora represent the domains of this body of knowledge. The goal of this research is to identify the major biological topics/concepts from a corpus of protein-related MEDLINE titles and abstracts by applying a probabilistic topic model. RESULTS: The latent Dirichlet allocation (LDA) model was applied to the corpus. Based on the Bayesian model selection, 300 major topics were extracted from the corpus. The majority of identified topics/concepts was found to be semantically coherent and most represented biological objects or concepts. The identified topics/concepts were further mapped to the controlled vocabulary of the Gene Ontology (GO) terms based on mutual information. CONCLUSION: The major and recurring biological concepts within a collection of MEDLINE documents can be extracted by the LDA model. The identified topics/concepts provide parsimonious and semantically-enriched representation of the texts in a semantic space with reduced dimensionality and can be used to index text.

Abstracting and Indexing↗
PubMed2006

The success (or not) of HUGO nomenclature.

Current usage of gene nomenclature is ambiguous and impairs the efficient handling of scientific information. Therefore it is important to propose guidelines to deal with this problem. This study attempts to evaluate the success of HUGO nomenclature for human genes. The results indicate that HUGO guidelines are not supported by the scientific community.

Genes↗
PubMed2004

MOSAIC acronym.

Explore the source record for details and available documents.

Acute Disease↗
PubMed2006

Taxonomic informatics tools for the electronic Nomenclator Zoologicus.

Given the current trends, it seems inevitable that all biological documents will eventually exist in a digital format and be distributed across the internet. New network services and tools need to be developed to increase retrieval rates for documents and to refine data recovery. Biological data have traditionally been well managed using taxonomic principles. As part of a larger initiative to build an array of names-based network services that emulate taxonomic principles for managing biological information, we undertook the digitization of a major taxonomic reference text, Nomenclator Zoologicus. The process involved replicating the text to a high level of fidelity, parsing the content for inclusion within a database, developing tools to enable expert input into the product, and integrating the metadata and factual content within taxonomic network services. The result is a high-quality and freely available web application (http://uio.mbl.edu/NomenclatorZoologicus/) capable of being exploited in an array of biological informatics services.

Animals↗
PubMed2001

Vitamins, herbs, and supplements: tools of empowerment.

1. Consumers who elect to use natural products are electing to do more than simply use a product. Their choice is an act of self-empowerment. 2. Education is necessary because these products most often are not being obtained in a professional, consultative setting but rather in chain discount department stores and supermarkets. 3. If consumers choose to address their health concerns using a natural-based treatment plan, consultation with a health care practitioner who shares this shift in perspective and who follows the literature is important. 4. A paradigm shift could be on the health care horizon, which when complete would make herbs and other natural products part of mainstream health care practice.

Dietary Supplements↗