Showing papers in "Journal of Biomedical Informatics in 2009"

TL;DR: Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data Capture tools to support clinical and translational research.

TL;DR: This review focuses on the recently renewed interest in development of fundamental NLP methods and advances in the NLP systems for CDS, and the current solutions to challenges posed by distinct sublanguages, intended user groups, and support goals.

TL;DR: In this study, it is found that ConText obtains reasonable to good performance for negated, historical, and hypothetical conditions across all report types that contain such conditions.

TL;DR: A review of the available methodologies for derivation of semantic relatedness from free text, as well as their evaluation in a variety of biomedical and other applications can be found in this article.

TL;DR: This study presents an original method for quantification and classification of erythrocytes in stained thin blood films infected with Plasmodium falciparum, which showed a specificity of 99.7% and a sensitivity of 94%.

TL;DR: An extensible and modifiable knowledge representation model to represent cancer disease characteristics in a comparable and consistent fashion is introduced and a gold-standard corpus of manually annotated colon cancer pathology reports is developed.

TL;DR: The construction of a semantically annotated corpus of clinical texts for use in the development and evaluation of systems for automatically extracting clinically significant information from the textual component of patient records is described.

TL;DR: The results suggest that multivariate time series models can be used to reliably forecast ED patient census; however, forecasts of the demands for diagnostic resources were not sufficiently reliable to be useful in the clinical setting.

TL;DR: Empirical studies conducted over two decades on the role of memory, knowledge organization and reasoning as well as studies of problem-solving and decision-making in medical areas that inform curricular design are summarized.

TL;DR: This paper provides a study on word clustering and selection based feature reduction approaches for named entity recognition using a maximum entropy classifier and the performance is found to be superior to existing systems which do not use domain knowledge.

TL;DR: An extensive literature review is performed to identify published descriptions of manual, systematic and heuristic methods that use knowledge (within or external to the terminology) to measure quality factors of different aspects of the terminology content (terms, semantic classification, and semantic relationships).

TL;DR: A rule-based information extraction (IE) system developed for Polish medical texts, which addressed such linguistic issues as: ambiguous keywords, negation, coordination or anaphoric expressions is described.

TL;DR: The case for Web 2.0 as a tool for collaborating on clinical decision support content appears strong, particularly for collaborative content development within an organization.

TL;DR: The experiments show that the GO Fuzzy c-means method can produce far better biologically meaningful clusters even with the use of a small percentage of Gene Ontology annotations, and indicates that the utilization of prior knowledge in the method can predict gene functions effectively.

TL;DR: This paper presents an evaluation methodology for LBD systems that allows comparisons across different systems and demonstrates the abilities of this evaluation methodology by using it to compare the performance of different correlation-mining and ranking approaches used by existing LBD system.

TL;DR: Semantic Web technologies are used to specify clinical archetypes for advanced EHR architectures and the advantages of using the Ontology Web Language (OWL) instead of ADL are described and discussed in this work.

TL;DR: After presenting a semantic abstraction automatic summarization system for MEDLINE citations, this work focuses on evaluating its ability to identify useful drug interventions for 53 diseases.

TL;DR: The National Cancer Institute Enterprise Vocabulary Services (NCI EVS) uses a wide range of quality assurance (QA) techniques to maintain and extend NCI Thesaurus (NCIt).

TL;DR: Enhanced performance from classification algorithms can be attained with the use of synthetic minority class oversampling techniques in sparse clinical datasets, and predictive models created in this manner can be used to develop evidence based ADE monitoring systems.

TL;DR: Various GIS based functionalities for health studies and their scope in analyzing and controlling epidemiological diseases are explored and the general management problems, issues and challenges related to HIV/AIDS prevailing in India are concluded.

TL;DR: Clinicians design their own information tools based on the existing health information technologies to meet their information needs and the characteristics of these clinician-designed tools provide insights into the "realities" of how clinicians work with health information Technologies.

TL;DR: A literature mining method for identification of relations between biomedical concepts in disconnected sets of articles called RaJoLink is developed and it is confirmed that the discovered relations might contribute to a better understanding of autism.

TL;DR: A controlled methodology, inspired by neuropsychological assessment tasks and embodied cognition, to develop cognitive simulators for laparoscopic surgery is described and the results of two pilot studies are presented that show the validity of the methodology in providing an effective evaluation and learning environments for surgeons.

TL;DR: This review will provide an overview of the current state of knowledge of both symmetry axis/plane detection, and asymmetry quantification in neuro-images.

TL;DR: The study demonstrates that this new scheme achieves higher and robust performance in classifying chromosomes and reduces the complexity of automated karyotyping scheme and improve its performance and robustness.

TL;DR: The conclusion is that porting newspaper parsers to the biomedical domain, at least for parsers which use lexicalized grammars, may not be as difficult as first thought.

TL;DR: Natural Language Processing, statistical, and machine learning methods of producing automatic MeSH main heading/subheading pair recommendations were assessed independently and combined and a suitable combination was integrated into MTI as a subheading attachment feature producing MeSH indexing recommendations compliant with current state-of-the-art indexing practice.

TL;DR: A computational method is proposed to discover the functional miRNA-mRNA regulatory modules (FMRMs), that is, groups of miRNAs and their target mRNAs that are believed to participate cooperatively in post-transcriptional gene regulation under specific conditions.

TL;DR: The Prostate Cancer Ontology (PCO) is created and applied to demonstrate how the ontology is utilized to solve the semantic heterogeneity problem from the integration of two prostate cancer related database systems at the Fox Chase Cancer Center.

TL;DR: This special issue is the first in any journal to deal exclusively with the auditing of medical terminologies and ontologies, and the intention is to capture the current state of the art in the field of terminology auditing.