A System for Identifying Named Entities in Biomedical Text: how Results From two Evaluations Reflect on Both the System and the Evaluations

We present a maximum entropy-based system for identifying named entities (NEs) in biomedical abstracts and present its performance in the only two biomedical named entity recognition (NER) comparative evaluations that have been held to date, namely BioCreative and Coling BioNLP. Our system obtained an exact match F-score of 83.2% in the BioCreative evaluation and 70.1% in the BioNLP evaluation. We discuss our system in detail, including its rich use of local features, attention to correct boundary identification, innovative use of external knowledge resources, including parsing and web searches, and rapid adaptation to new NE sets. We also discuss in depth problems with data annotation in the evaluations which caused the final performance to be lower than optimal

Exploring the boundaries: gene and protein identification in biomedical text

Background: Good automatic information extraction tools offer hope for automatic processing of the exploding biomedical literature, and successful named entity recognition is a key component for such tools. Methods: We present a maximum-entropy based system incorporating a diverse set of features for identifying gene and protein names in biomedical abstracts. Results: This system was entered in the BioCreative comparative evaluation and achieved a precision of 0.83 and recall of 0.84 in the “open ” evaluation and a precision of 0.78 and recall of 0.85 in the “closed ” evaluation. Conclusions: Central contributions are rich use of features derived from the training data at multiple levels of granularity, a focus on correctly identifying entity boundaries, and the innovative use of several external knowledge sources including full MEDLINE abstracts and web searches. Background The explosion of information in the biomedical domain and particularly in genetics has highlighted the need for automated text information extraction techniques. MEDLINE, the primary research database serving the biomedical community, currently contains over 14 million abstracts, with 60,000 new abstracts appearing each month. There is also an impressive number of molecular biological databases covering a

The implementation of the serial trial intervention for pain and challenging behaviour in advanced dementia patients (STA OP!): a clustered randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Pain (physical discomfort) and challenging behaviour are highly prevalent in nursing home residents with dementia: at any given time 45-80% of nursing home residents are in pain and up to 80% have challenging behaviour. In the USA Christine Kovach developed the serial trial intervention (STI) and established that this protocol leads to less discomfort and fewer behavioural symptoms in moderate to severe dementia patients. The present study will provide insight into the effects of implementation of the Dutch version of the STI-protocol (STA OP!) in comparison with a control intervention, not only on behavioural symptoms, but also on pain, depression, and quality of life. This article outlines the study protocol.</p> <p>Methods/Design</p> <p>The study is a cluster randomized controlled trial in 168 older people (aged >65 years) with mild or moderate dementia living in nursing homes. The clusters, Dutch nursing homes, are randomly assigned to either the intervention condition (training and implementation of the STA OP!-protocol) or the control condition (general training focusing on challenging behaviour and pain, but without the step-wise approach). Measurements take place at baseline, after 3 months (end of the STA OP! training period) and after 6 months.</p> <p>Primary outcome measures are symptoms of challenging behaviour (measured with the Cohen-Mansfield Agitation Inventory (CMAI) and the Neuropsychiatric Inventory-Nursing Home version (NPI-NH)), and pain (measure with the Dutch version of the Pain Assessment Checklist for Seniors (PACSLAC-D) and the Minimum Data Set of the Resident Assessment Instrument (MDS-RAI) pain scale). Secondary outcome measures include symptoms of depression (Cornell and MDS-RAI depression scale), Quality of Live (Qualidem), changes in prescriptions of analgesics and psychotropic drugs, and the use of non-pharmacological comfort interventions (e.g. snoezelen, reminiscence therapy).</p> <p>Discussion</p> <p>The transfer from the American design to the Dutch design involved several changes due to the different organisation of healthcare systems. Specific strengths and limitations of the study are discussed.</p> <p>Trial registration</p> <p>Netherlands Trial Register (NTR): <a href="http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=1967">NTR1967</a></p

C. elegans VANG-1 Modulates Life Span via Insulin/IGF-1-Like Signaling

The planar cell polarity (PCP) pathway is highly conserved from Drosophila to humans and a PCP-like pathway has recently been described in the nematode Caenorhabditis elegans. The developmental function of this pathway is to coordinate the orientation of cells or structures within the plane of an epithelium or to organize cell-cell intercalation required for correct morphogenesis. Here, we describe a novel role of VANG-1, the only C. elegans ortholog of the conserved PCP component Strabismus/Van Gogh. We show that two alleles of vang-1 and depletion of the protein by RNAi cause an increase of mean life span up to 40%. Consistent with the longevity phenotype vang-1 animals also show enhanced resistance to thermal- and oxidative stress and decreased lipofuscin accumulation. In addition, vang-1 mutants show defects like reduced brood size, decreased ovulation rate and prolonged reproductive span, which are also related to gerontogenes. The germline, but not the intestine or neurons, seems to be the primary site of vang-1 function. Life span extension in vang-1 mutants depends on the insulin/IGF-1-like receptor DAF-2 and DAF-16/FoxO transcription factor. RNAi against the phase II detoxification transcription factor SKN-1/Nrf2 also reduced vang-1 life span that might be explained by gradual inhibition of insulin/IGF-1-like signaling in vang-1. This is the first time that a key player of the PCP pathway is shown to be involved in the insulin/IGF-1-like signaling dependent modulation of life span in C. elegans

Handbook of Active Ageing and Quality of Life: From Concepts to Applications

La edición de este libro estuvo a cargo de Fermina Rojo-Pérez y Gloria Fernández-Mayoralas.El documento adjunto contiene la cubierta, portada e índice del libro.This handbook presents an overview of studies on the relationship of active ageing and quality of life. It addresses the new challenges of ageing from the paradigm of positive ageing (active, healthy and successful) for a better quality of life. It provides theoretical perspectives and empirical studies, including scientific knowledge as well as practical experiences about the good ageing and the quality of later life around the world, in order to respond to the challenges of an aged population. The handbook is structured in 4 sections covering theoretical and conceptual perspectives, social policy issues and research agenda, methods, measurement instrument-scales and evaluations, and lastly application studies including domains and geographical contexts.Peer reviewe

Hierarchical Bayesian Domain Adaptation

Multi-task learning is the problem of maximizing the performance of a system across a number of related tasks. When applied to multiple domains for the same task, it is similar to domain adaptation, but symmetric, rather than limited to improving performance on a target domain. We present a more principled, better performing model for this problem, based on the use of a hierarchical Bayesian prior. Each domain has its own domain-specific parameter for each feature but, rather than a constant prior over these parameters, the model instead links them via a hierarchical Bayesian global prior. This prior encourages the features to have similar weights across domains, unless there is good evidence to the contrary. We show that the method of (Daumé III, 2007), which was presented as a simple “preprocessing step, ” is actually equivalent, except our representation explicitly separates hyperparameters which were tied in his work. We demonstrate that allowing different values for these hyperparameters significantly improves performance over both a strong baseline and (Daumé III, 2007) within both a conditional random field sequence model for named entity recognition and a discriminatively trained dependency parser.

Solving the problem of cascading errors

The end-to-end performance of natural language processing systems for compound tasks, such as question answering and textual entailment, is often hampered by use of a greedy 1-best pipeline architecture, which causes errors to propagate and compound at each stage. We present a novel architecture, which models these pipelines as Bayesian networks, with each low level task corresponding to a variable in the network, and then we perform approximate inference to find the best labeling. Our approach is extremely simple to apply but gains the benefits of sampling the entire distribution over labels at each stage in the pipeline. We apply our method to two tasks -- semantic role labeling and recognizing textual entailment -- and achieve useful performance gains from the superior pipeline architecture