Using ontology in query answering systems: Scenarios, requirements and challenges

Equipped with the ultimate query answering system, computers would finally be in a position to address all our information needs in a natural way. In this paper, we describe how Language and Computing nv (L&C), a developer of ontology-based natural language understanding systems for the healthcare domain, is working towards the ultimate Question Answering (QA) System for healthcare workers. L&C’s company strategy in this area is to design in a step-by-step fashion the essential components of such a system, each component being designed to solve some one part of the total problem and at the same time reflect well-defined needs on the prat of our customers. We compare our strategy with the research roadmap proposed by the Question Answering Committee of the National Institute of Standards and Technology (NIST), paying special attention to the role of ontology

Briefing paper 'On the European workforce for health'

A critique of the EC report 'On the European Workforce for Health', together with workshop conclusions

Fluctuat nec mergitur or what happened to Reikian psychoanalysis?

The official published version can be obtained from the link below - Copyright @ 2006 American Psychological AssociationAlthough Theodor Reik was a celebrated psychoanalyst during the 1950s and 1960s, his work has not resulted in the development of a specific psychoanalytic tradition, and his name has gradually disappeared from Western cultural memory. Following the mode of argumentation of the reductio ad absurdum, the author critically examines six possible explanations for this remarkable observation, thereby drawing on published materials and archival sources relating to the life and works of Reik. Once these explanations have been discarded, the author argues that the main reason for the absence of a Reikian tradition within psychoanalysis stems from Reik's belief in the analytic virtue of intellectual independence. This belief may have contributed to his own departure from the psychoanalytic training institution that he helped to create, yet it also implies that Reikian psychoanalysis somehow lives on in all those practitioners who do not seek to affiliate with a doctrinal school of thought

Using Neural Networks for Relation Extraction from Biomedical Literature

Using different sources of information to support automated extracting of relations between biomedical concepts contributes to the development of our understanding of biological systems. The primary comprehensive source of these relations is biomedical literature. Several relation extraction approaches have been proposed to identify relations between concepts in biomedical literature, namely, using neural networks algorithms. The use of multichannel architectures composed of multiple data representations, as in deep neural networks, is leading to state-of-the-art results. The right combination of data representations can eventually lead us to even higher evaluation scores in relation extraction tasks. Thus, biomedical ontologies play a fundamental role by providing semantic and ancestry information about an entity. The incorporation of biomedical ontologies has already been proved to enhance previous state-of-the-art results.Comment: Artificial Neural Networks book (Springer) - Chapter 1

Doctor of Philosophy

dissertationMedical knowledge learned in medical school can become quickly outdated given the tremendous growth of the biomedical literature. It is the responsibility of medical practitioners to continuously update their knowledge with recent, best available clinical evidence to make informed decisions about patient care. However, clinicians often have little time to spend on reading the primary literature even within their narrow specialty. As a result, they often rely on systematic evidence reviews developed by medical experts to fulfill their information needs. At the present, systematic reviews of clinical research are manually created and updated, which is expensive, slow, and unable to keep up with the rapidly growing pace of medical literature. This dissertation research aims to enhance the traditional systematic review development process using computer-aided solutions. The first study investigates query expansion and scientific quality ranking approaches to enhance literature search on clinical guideline topics. The study showed that unsupervised methods can improve retrieval performance of a popular biomedical search engine (PubMed). The proposed methods improve the comprehensiveness of literature search and increase the ratio of finding relevant studies with reduced screening effort. The second and third studies aim to enhance the traditional manual data extraction process. The second study developed a framework to extract and classify texts from PDF reports. This study demonstrated that a rule-based multipass sieve approach is more effective than a machine-learning approach in categorizing document-level structures and iv that classifying and filtering publication metadata and semistructured texts enhances the performance of an information extraction system. The proposed method could serve as a document processing step in any text mining research on PDF documents. The third study proposed a solution for the computer-aided data extraction by recommending relevant sentences and key phrases extracted from publication reports. This study demonstrated that using a machine-learning classifier to prioritize sentences for specific data elements performs equally or better than an abstract screening approach, and might save time and reduce errors in the full-text screening process. In summary, this dissertation showed that there are promising opportunities for technology enhancement to assist in the development of systematic reviews. In this modern age when computing resources are getting cheaper and more powerful, the failure to apply computer technologies to assist and optimize the manual processes is a lost opportunity to improve the timeliness of systematic reviews. This research provides methodologies and tests hypotheses, which can serve as the basis for further large-scale software engineering projects aimed at fully realizing the prospect of computer-aided systematic reviews

ATXN2-CAG42 sequesters PABPC1 into insolubility and induces FBXW8 in cerebellum of old ataxic knock-in mice

Spinocerebellar Ataxia Type 2 (SCA2) is caused by expansion of a polyglutamine encoding triplet repeat in the human ATXN2 gene beyond (CAG)31. This is thought to mediate toxic gain-of-function by protein aggregation and to affect RNA processing, resulting in degenerative processes affecting preferentially cerebellar neurons. As a faithful animal model, we generated a knock-in mouse replacing the single CAG of murine Atxn2 with CAG42, a frequent patient genotype. This expansion size was inherited stably. The mice showed phenotypes with reduced weight and later motor incoordination. Although brain Atxn2 mRNA became elevated, soluble ATXN2 protein levels diminished over time, which might explain partial loss-of-function effects. Deficits in soluble ATXN2 protein correlated with the appearance of insoluble ATXN2, a progressive feature in cerebellum possibly reflecting toxic gains-of-function. Since in vitro ATXN2 overexpression was known to reduce levels of its protein interactor PABPC1, we studied expansion effects on PABPC1. In cortex, PABPC1 transcript and soluble and insoluble protein levels were increased. In the more vulnerable cerebellum, the progressive insolubility of PABPC1 was accompanied by decreased soluble protein levels, with PABPC1 mRNA showing no compensatory increase. The sequestration of PABPC1 into insolubility by ATXN2 function gains was validated in human cell culture. To understand consequences on mRNA processing, transcriptome profiles at medium and old age in three different tissues were studied and demonstrated a selective induction of Fbxw8 in the old cerebellum. Fbxw8 is encoded next to the Atxn2 locus and was shown in vitro to decrease the level of expanded insoluble ATXN2 protein. In conclusion, our data support the concept that expanded ATXN2 undergoes progressive insolubility and affects PABPC1 by a toxic gain-of-function mechanism with tissuespecific effects, which may be partially alleviated by the induction of FBXW8

Electronic health record standards

Objectives: This paper seeks to provide an overview of the initiatives that are proceeding internationally to develop standards for the exchange of electronic health record (EHR) information between EHR systems.Methods: The paper reviews the clinical and ethico-legal requirements and research background on the representation and communication of EHR data, which primarily originates from Europe through a series of EU funded Health Telematics projects over the post thirteen years. The major concept that underpin the information models and knowledge models are summarised. These provide the requirements and the best evidential basis from which HER communications standards should be developed.Results. The main focus of EHR communications standardisation is presently occurring at a European level, through the Committee for European Normalisation (CEN). The major constructs of the CEN 13606 model ate outlined. Complementary activity is taking place in ISO and in HL7, and some of these efforts are also summarised.Conclusior: There is a strong prospect that a generic EHR interoperability standard can be agreed at a European (and hopefully international) level. Parts of the challenge of EHR i interoperability cannot yet he standardised, because good solutions to the preservation of clinical meaning across heterogeneous systems remain to be explored. Further research and empirical projects are therefore also needed