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Nosology and vital statistics of dementing conditions of elderly people.
The nosology of dementing conditions of very old people, as described in the International Classification of Diseases, Ninth Revision (ICD-9) and reported in Vital Statistics of the United States, is examined. Methods included a questionnaire of state officials who oversee death certification that asked chiefly about death certificate entries that denote dementing conditions. Current nosology includes several dementing conditions that are commonly indistinguishable without a postmortem examination. Dementing conditions are grouped with other conditions of unrelated pathogenesis. The words "psychosis" and "dementia" are used interchangeably. The majority of state officials said that some death certificate entries denoting dementing conditions are acceptable as causes of death. The current system of nosology of dementing conditions probably results in the under-reporting of these conditions in vital statistics. The tenth revision of the International Classification of Diseases (ICD-10) classifies dementing conditions similarly to the ninth revision. An alternative system of nosology, based on dementia as a common characteristic, is suggested.
Introduction and overview. Statistical methods in genetic epidemiology.
Common terms used in genetics with multiple meanings are explained and a brief overview given of the four major areas of genetic epidemiology--the study of familial aggregation, segregation, cosegregation and association. Familial aggregation measures the potential for a trait to have a genetic aetiology. Segregation analysis uncovers single gene segregation. Cosegregation with genetic markers gives rise to linkage, which is used to locate trait genes on the genome. Association analysis is used for fine mapping, but rests on the assumption that linkage disequilibrium exists.
Myelodysplastic syndromes standardized response criteria: further definition.
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Inconsistencies over time in 5% of NetAffx probe-to-gene annotations.
BACKGROUND: DNA microarray probes are designed to match particular mRNA transcripts, often based on expressed sequences like ESTs, or cDNAs, many times incomplete. As a result, the relations between probes and genes can change as the sequence data are updated. However, it is frequent that the reported results of microarray analyses are given just as lists of genes without any reference to the underlying probes. RESULTS: We show for a particular commercial microarray design that the number of probes associated to some genes change with time. These changes concern approximately 5% of the probe sets across the history of annotation releases over a two year span. CONCLUSION: We recommend to report probe set identifiers when publishing microarray results, and to submit those analyses to microarray public databases to ensure that the interpretation of the data is updated with the latest set of annotations.
Evaluation of BioCreAtIvE assessment of task 2.
BACKGROUND: Molecular Biology accumulated substantial amounts of data concerning functions of genes and proteins. Information relating to functional descriptions is generally extracted manually from textual data and stored in biological databases to build up annotations for large collections of gene products. Those annotation databases are crucial for the interpretation of large scale analysis approaches using bioinformatics or experimental techniques. Due to the growing accumulation of functional descriptions in biomedical literature the need for text mining tools to facilitate the extraction of such annotations is urgent. In order to make text mining tools useable in real world scenarios, for instance to assist database curators during annotation of protein function, comparisons and evaluations of different approaches on full text articles are needed. RESULTS: The Critical Assessment for Information Extraction in Biology (BioCreAtIvE) contest consists of a community wide competition aiming to evaluate different strategies for text mining tools, as applied to biomedical literature. We report on task two which addressed the automatic extraction and assignment of Gene Ontology (GO) annotations of human proteins, using full text articles. The predictions of task 2 are based on triplets of protein--GO term--article passage. The annotation-relevant text passages were returned by the participants and evaluated by expert curators of the GO annotation (GOA) team at the European Institute of Bioinformatics (EBI). Each participant could submit up to three results for each sub-task comprising task 2. In total more than 15,000 individual results were provided by the participants. The curators evaluated in addition to the annotation itself, whether the protein and the GO term were correctly predicted and traceable through the submitted text fragment. CONCLUSION: Concepts provided by GO are currently the most extended set of terms used for annotating gene products, thus they were explored to assess how effectively text mining tools are able to extract those annotations automatically. Although the obtained results are promising, they are still far from reaching the required performance demanded by real world applications. Among the principal difficulties encountered to address the proposed task, were the complex nature of the GO terms and protein names (the large range of variants which are used to express proteins and especially GO terms in free text), and the lack of a standard training set. A range of very different strategies were used to tackle this task. The dataset generated in line with the BioCreative challenge is publicly available and will allow new possibilities for training information extraction methods in the domain of molecular biology.
Finding genomic ontology terms in text using evidence content.
BACKGROUND: The development of text mining systems that annotate biological entities with their properties using scientific literature is an important recent research topic. These systems need first to recognize the biological entities and properties in the text, and then decide which pairs represent valid annotations. METHODS: This document introduces a novel unsupervised method for recognizing biological properties in unstructured text, involving the evidence content of their names. RESULTS: This document shows the results obtained by the application of our method to BioCreative tasks 2.1 and 2.2, where it identified Gene Ontology annotations and their evidence in a set of articles. CONCLUSION: From the performance obtained in BioCreative, we concluded that an automatic annotation system can effectively use our method to identify biological properties in unstructured text.
Exploring supervised and unsupervised methods to detect topics in biomedical text.
BACKGROUND: Topic detection is a task that automatically identifies topics (e.g., "biochemistry" and "protein structure") in scientific articles based on information content. Topic detection will benefit many other natural language processing tasks including information retrieval, text summarization and question answering; and is a necessary step towards the building of an information system that provides an efficient way for biologists to seek information from an ocean of literature. RESULTS: We have explored the methods of Topic Spotting, a task of text categorization that applies the supervised machine-learning technique naïve Bayes to assign automatically a document into one or more predefined topics; and Topic Clustering, which apply unsupervised hierarchical clustering algorithms to aggregate documents into clusters such that each cluster represents a topic. We have applied our methods to detect topics of more than fifteen thousand of articles that represent over sixteen thousand entries in the Online Mendelian Inheritance in Man (OMIM) database. We have explored bag of words as the features. Additionally, we have explored semantic features; namely, the Medical Subject Headings (MeSH) that are assigned to the MEDLINE records, and the Unified Medical Language System (UMLS) semantic types that correspond to the MeSH terms, in addition to bag of words, to facilitate the tasks of topic detection. Our results indicate that incorporating the MeSH terms and the UMLS semantic types as additional features enhances the performance of topic detection and the naïve Bayes has the highest accuracy, 66.4%, for predicting the topic of an OMIM article as one of the total twenty-five topics. CONCLUSION: Our results indicate that the supervised topic spotting methods outperformed the unsupervised topic clustering; on the other hand, the unsupervised topic clustering methods have the advantages of being robust and applicable in real world settings.
New directions in biomedical text annotation: definitions, guidelines and corpus construction.
BACKGROUND: While biomedical text mining is emerging as an important research area, practical results have proven difficult to achieve. We believe that an important first step towards more accurate text-mining lies in the ability to identify and characterize text that satisfies various types of information needs. We report here the results of our inquiry into properties of scientific text that have sufficient generality to transcend the confines of a narrow subject area, while supporting practical mining of text for factual information. Our ultimate goal is to annotate a significant corpus of biomedical text and train machine learning methods to automatically categorize such text along certain dimensions that we have defined. RESULTS: We have identified five qualitative dimensions that we believe characterize a broad range of scientific sentences, and are therefore useful for supporting a general approach to text-mining: focus, polarity, certainty, evidence, and directionality. We define these dimensions and describe the guidelines we have developed for annotating text with regard to them. To examine the effectiveness of the guidelines, twelve annotators independently annotated the same set of 101 sentences that were randomly selected from current biomedical periodicals. Analysis of these annotations shows 70-80% inter-annotator agreement, suggesting that our guidelines indeed present a well-defined, executable and reproducible task. CONCLUSION: We present our guidelines defining a text annotation task, along with annotation results from multiple independently produced annotations, demonstrating the feasibility of the task. The annotation of a very large corpus of documents along these guidelines is currently ongoing. These annotations form the basis for the categorization of text along multiple dimensions, to support viable text mining for experimental results, methodology statements, and other forms of information. We are currently developing machine learning methods, to be trained and tested on the annotated corpus, that would allow for the automatic categorization of biomedical text along the general dimensions that we have presented. The guidelines in full detail, along with annotated examples, are publicly available.
Systematic reviews of epidemiology in diabetes: finding the evidence.
BACKGROUND: Methodological research to support searching for those doing systematic reviews of epidemiological studies is a relatively neglected area. Our aim was to determine how many databases it is necessary to search to ensure a comprehensive coverage of the literature in diabetes epidemiology, with the aim of examining the efficiency of searching in support of systematic reviews of the epidemiology of diabetes METHODS: Three approaches were used. First, we defined a set of English language diabetes journals and examined their coverage in bibliographic databases. Second, we searched extensively for diabetes epidemiology articles (in all languages) to determine which are the most useful databases; and third, we analysed the scattering of these articles to determine the core journals in the area. RESULTS: The overlap between MEDLINE and Embase for diabetes journals was 59%. A search for diabetes epidemiology articles across both MEDLINE and Embase, showed that MEDLINE alone retrieved about 94% of the total articles. Searching for diabetes epidemiology studies beyond MEDLINE and Embase retrieved no additional English language journal articles. The only diabetes epidemiology studies found by searching beyond MEDLINE and Embase were found in LILACS, and were Spanish or Portuguese language studies from Latin America; no additional English language studies were found. Only 30% of the meeting abstracts were converted to full publication after three years. One third of journal articles were published in just six journals, with Diabetes Care contributing 14.3% of the articles, followed by Diabetic Medicine (5.0%); Diabetes Research & Clinical Practice (4.1%); Diabetologia (4.0%); Diabetes & Metabolism (2.4%) and Diabetes (2.0%). CONCLUSIONS: Our results show that when searching for articles on diabetes epidemiology, MEDLINE and Embase would suffice for English language papers, with LILACS giving some additional non-English articles from Latin America. Although a MEDLINE-only search will retrieve the vast majority of the relevant literature, Embase and LILACs should also be searched to ensure the search is comprehensive. Searching for meeting abstracts is recommended to alert reviewers to unpublished work. The low rate of full publication of meeting abstracts has the danger of producing bias in reviews. Our findings on scattering show that the core literature in this field is concentrated in just six journals.
Proposal for a new name as well as having the new WHO definition of palliative care.
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Multiple personality disorder.
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Intensity-modulated radiotherapy in the standard management of head and neck cancer: promises and pitfalls.
The purpose of this article is to review the role of intensity-modulated radiotherapy (IMRT) in the standard management of patients with head and neck cancer through a critical review of the pertinent literature. IMRT may result in a dose distribution that is more conformal than that achieved with three-dimensional conformal radiotherapy (3D CRT), allowing dose reduction to normal structures and thus decreasing toxicity and possibly enhancing locoregional control through dose escalation. Disadvantages associated with IMRT include increased risk of a marginal miss, decreased dose homogeneity, increased total body dose, and increased labor and expense. Outcomes data after IMRT are limited, and follow-up is relatively short. Locoregional control rates appear to be comparable to those achieved with 3D CRT and, depending on the location and extent of the tumor, late toxicity may be lower. Despite limited data on clinical outcomes, IMRT has been widely adopted as a standard technique in routine practice and clinical trials. The use of IMRT involves a learning curve for the practitioner and will continue to evolve, requiring continuing education and monitoring of outcomes from routine practice. Additional standards pertaining to a variety of issues, including target definitions and dose specification, need to be developed. Phase III trials will better define the role of IMRT in coming years.
Development of guidelines for idiopathic normal-pressure hydrocephalus: introduction.
OBJECTIVE: There are no currently accepted evidence-based guidelines for the diagnosis and management of the normal-pressure hydrocephalus (NPH) patient. As a result, an independent study group was assembled to address this issue and determine the feasibility of developing standardized guidelines, which would be acceptable in the United States and abroad and would be based on the available scientific evidence. The guidelines were to encompass value of clinical presentation, value of supplementary diagnostic tests, surgical management, and outcome assessment. METHODS: Initially, a series of 10 questions were formulated in the areas of pathophysiology, diagnosis, and treatment to obtain a consensus by panels of experts (see Acknowledgments) assembled in San Antonio, TX, in September 2000. This workshop provided significant insight into the difficulties in developing NPH guidelines, and a consensus was reached as to those questions involving expert opinion. Subsequently, evidentiary tables were developed on the basis of the available evidence. Only those studies with 20 or more idiopathic NPH (INPH) patients were included. RESULTS: Sensitivity, specificity, and positive and negative predictive values for INPH diagnostic criteria were assessed, and guidelines were developed on the basis of the available evidence. Recommendations for classification of INPH and additional studies were documented. CONCLUSION: The development of the guidelines was made difficult because systematic studies of INPH and patient numbers were few. It was decided to maintain the classification of NPH into two major categories, INPH and those of known cause (secondary NPH). Many studies "mixed" these classifications, and as a result, they could not be used in the evidentiary tables. Despite these problems, evidence-based guidelines were developed, and it is hoped that they will be useful in guiding clinical management of the INPH patient.
Concussion (mild traumatic brain injury) and the team physician: a consensus statement.
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Concussion (mild traumatic brain injury) and the team physician: a consensus statement.
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So you want to do research? 1: an overview of the research process.
Relative to some other health care professionals, nursing has an immature research tradition as well as a limited body of research-based knowledge to draw on. Nevertheless, research is important to the nursing profession which over the past 15 years has increasingly had pressure placed on it to be more accountable for its actions. Research is also important so as to answer specific and broader clinical questions. This article, the first in series of seven, is aimed to provide novice researchers with an overview of the research process, with a specific focus on developing the research question, undertaking a review of the literature, describing the different research methodologies, sample size, data collection methods and analysis. Different approaches for ensuring more effective dissemination of research findings to different audiences are also briefly discussed.