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    1. Natural language processing using online analytic processing for assessing recommendations in radiology reports.

      Related Articles Natural language processing using online analytic processing for assessing recommendations in radiology reports. J Am Coll Radiol. 2008 Mar;5(3):197-204 Authors: Dang PA, Kalra MK, Blake MA, Schultz TJ, Stout M, Lemay PR, Freshman DJ, Halpern EF, Dreyer KJ PURPOSE: The study purpose was to describe the use of natural language processing (NLP) and online analytic processing (OLAP) for assessing patterns in recommendations in unstructured radiology reports on the basis of patient and imaging characteristics, such as age, gender, referring physicians, radiology subspecialty, modality, indications, diseases, and patient status (inpatient vs outpatient). MATERIALS AND METHODS: A ...
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    2. Semantic tagging for medical knowledge tracking.

      Related Articles Semantic tagging for medical knowledge tracking. Conf Proc IEEE Eng Med Biol Soc. 2006;1:6257-60 Authors: Jang H, Song SK, Myaeng SH We propose a semantic tagger that provides high level concept information for phrases in clinical documents, which enriches medical information tracking system that support decision making or quality assurance of medical treatment. In this paper, we have tried to deal with patient records written by doctors rather than well-formed documents such as Medline abstracts. In addition, annotating clinical text on phrases semantically rather than syntactically has been attempted, which are at higher level granularity than ...
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    3. BioProber: software system for biomedical relation discovery from PubMed.

      Related Articles BioProber: software system for biomedical relation discovery from PubMed. Conf Proc IEEE Eng Med Biol Soc. 2006;1:5779-82 Authors: Jang H, Lim J, Lim JH, Park SJ, Lee KC The numbers of articles and journals that are published are increasing at a considerable rate, and the published information is growing continuously and fast. Because of this, researches to acquire knowledge automatically have been carried out in the areas of information retrieval, information extraction and text mining. Information retrieval approaches are good for specific topics that the number of related articles is small. But, if the number is ...
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    4. The AMIA 2006 Scientific Program Committee has retracted the following paper from the AMIA 2006 Proceedings: Comparative evaluation of accuracy of extraction of medication information from narrative physician notes by commercial and academic natural langu

      The AMIA 2006 Scientific Program Committee has retracted the following paper from the AMIA 2006 Proceedings: Comparative evaluation of accuracy of extraction of medication information from narrative physician notes by commercial and academic natural language processing software packages. AMIA Annu Symp Proc. 2006;:789-93 Authors: PMID: 18297753 [PubMed - in process]
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    5. Randomized controlled trial of an automated problem list with improved sensitivity.

      Related Articles Randomized controlled trial of an automated problem list with improved sensitivity. Int J Med Inform. 2008 Feb 14; Authors: Meystre SM, Haug PJ PURPOSE: To improve the completeness and timeliness of an electronic problem list, we have developed a system using Natural Language Processing (NLP) to automatically extract potential medical problems from clinical, free-text documents; these problems are then proposed for inclusion in an electronic problem list management application. METHODS: A prospective randomized controlled evaluation of the Automatic Problem List (APL) system in an intensive care unit and in a cardiovascular surgery unit is reported here. A total ...
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    6. Extraction of Protein Interaction Data: A Comparative Analysis of Methods in Use.

      Related Articles Extraction of Protein Interaction Data: A Comparative Analysis of Methods in Use. EURASIP J Bioinform Syst Biol. 2007;2007:53096 Authors: Jose H, Vadivukarasi T, Devakumar J Several natural language processing tools, both commercial and freely available, are used to extract protein interactions from publications. Methods used by these tools include pattern matching to dynamic programming with individual recall and precision rates. A methodical survey of these tools, keeping in mind the minimum interaction information a researcher would need, in comparison to manual analysis has not been carried out. We compared data generated using some of the selected ...
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      Mentions: India Bangalore
    7. Script and language identification in noisy and degraded document images.

      Related Articles Script and language identification in noisy and degraded document images. IEEE Trans Pattern Anal Mach Intell. 2008 Jan;30(1):14-24 Authors: Shijian L, Lim Tan C This paper reports an identification technique that detects scripts and languages of noisy and degraded document images. In the proposed technique, scripts and languages are identified through the document vectorization, which converts each document image into a document vector that characterizes the shape and frequency of the conta ned character or word images. Document images are vectorized by using vertical component cuts and character extremum points, which are both tolerant to ...
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    8. Comparison with manual registration reveals satisfactory completeness and efficiency of a computerized cancer registration system.

      Related Articles Comparison with manual registration reveals satisfactory completeness and efficiency of a computerized cancer registration system. J Biomed Inform. 2008 Feb;41(1):24-32 Authors: Contiero P, Tittarelli A, Maghini A, Fabiano S, Frassoldi E, Costa E, Gada D, Codazzi T, Crosignani P, Tessandori R, Tagliabue G Automated software for cancer registration, called Open Registry and developed by ourselves was adopted by the Varese (population-based) Cancer Registry starting from 1997. Since the use of automated cancer registration is increasing, it is important to assess the quality and completeness of the automated data being produced. In this study, we assessed ...
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    9. A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences.

      Related Articles A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences. J Biomed Inform. 2008 Feb;41(1):65-81 Authors: Othman RM, Deris S, Illias RM A genetic similarity algorithm is introduced in this study to find a group of semantically similar Gene Ontology terms. The genetic similarity algorithm combines semantic similarity measure algorithm with parallel genetic algorithm. The semantic similarity measure algorithm is used to compute the similitude strength between the Gene Ontology terms. Then, the parallel genetic algorithm is employed to perform batch retrieval and to accelerate the search in large search ...
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      Mentions: Gene Ontology
    10. Non-linear correlation of content and metadata information extracted from biomedical article datasets.

      Related Articles Non-linear correlation of content and metadata information extracted from biomedical article datasets. J Biomed Inform. 2008 Feb;41(1):202-16 Authors: Theodosiou T, Angelis L, Vakali A Biomedical literature databases constitute valuable repositories of up to date scientific knowledge. The development of efficient machine learning methods in order to facilitate the organization of these databases and the extraction of novel biomedical knowledge is becoming increasingly important. Several of these methods require the representation of the documents as vectors of variables forming large multivariate datasets. Since the amount of information contained in different datasets is voluminous, an open issue ...
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    11. PubMed related articles: a probabilistic topic-based model for content similarity.

      Related Articles PubMed related articles: a probabilistic topic-based model for content similarity. BMC Bioinformatics. 2007;8:423 Authors: Lin J, Wilbur WJ BACKGROUND: We present a probabilistic topic-based model for content similarity called pmra that underlies the related article search feature in PubMed. Whether or not a document is about a particular topic is computed from term frequencies, modeled as Poisson distributions. Unlike previous probabilistic retrieval models, we do not attempt to estimate relevance-but rather our focus is "relatedness", the probability that a user would want to examine a particular document given known interest in another. We also describe a ...
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    12. Identifying smokers with a medical extraction system.

      Related Articles Identifying smokers with a medical extraction system. J Am Med Inform Assoc. 2008 Jan-Feb;15(1):36-9 Authors: Clark C, Good K, Jezierny L, Macpherson M, Wilson B, Chajewska U The Clinical Language Understanding group at Nuance Communications has developed a medical information extraction system that combines a rule-based extraction engine with machine learning algorithms to identify and categorize references to patient smoking in clinical reports. The extraction engine identifies smoking references; documents that contain no smoking references are classified as UNKNOWN. For the remaining documents, the extraction engine uses linguistic analysis to associate features such as status ...
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    13. The evaluation of a temporal reasoning system in processing clinical discharge summaries.

      Related Articles The evaluation of a temporal reasoning system in processing clinical discharge summaries. J Am Med Inform Assoc. 2008 Jan-Feb;15(1):99-106 Authors: Zhou L, Parsons S, Hripcsak G CONTEXT: TimeText is a temporal reasoning system designed to represent, extract, and reason about temporal information in clinical text. OBJECTIVE: To measure the accuracy of the TimeText for processing clinical discharge summaries. DESIGN: Six physicians with biomedical informatics training served as domain experts. Twenty discharge summaries were randomly selected for the evaluation. For each of the first 14 reports, 5 to 8 clinically important medical events were chosen. The ...
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    14. Five-way smoking status classification using text hot-spot identification and error-correcting output codes.

      Related Articles Five-way smoking status classification using text hot-spot identification and error-correcting output codes. J Am Med Inform Assoc. 2008 Jan-Feb;15(1):32-5 Authors: Cohen AM We participated in the i2b2 smoking status classification challenge task. The purpose of this task was to evaluate the ability of systems to automatically identify patient smoking status from discharge summaries. Our submission included several techniques that we compared and studied, including hot-spot identification, zero-vector filtering, inverse class frequency weighting, error-correcting output codes, and post-processing rules. We evaluated our approaches using the same methods as the i2b2 task organizers, using micro- and macro-averaged ...
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    15. Text processing through Web services: calling Whatizit.

      Related Articles Text processing through Web services: calling Whatizit. Bioinformatics. 2008 Jan 15;24(2):296-8 Authors: Rebholz-Schuhmann D, Arregui M, Gaudan S, Kirsch H, Jimeno A MOTIVATION: Text-mining (TM) solutions are developing into efficient services to researchers in the biomedical research community. Such solutions have to scale with the growing number and size of resources (e.g. available controlled vocabularies), with the amount of literature to be processed (e.g. about 17 million documents in PubMed) and with the demands of the user community (e.g. different methods for fact extraction). These demands motivated the development of a server-based ...
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    16. Automated acquisition of disease drug knowledge from biomedical and clinical documents: an initial study.

      Related Articles Automated acquisition of disease drug knowledge from biomedical and clinical documents: an initial study. J Am Med Inform Assoc. 2008 Jan-Feb;15(1):87-98 Authors: Chen ES, Hripcsak G, Xu H, Markatou M, Friedman C OBJECTIVE: Explore the automated acquisition of knowledge in biomedical and clinical documents using text mining and statistical techniques to identify disease-drug associations. DESIGN: Biomedical literature and clinical narratives from the patient record were mined to gather knowledge about disease-drug associations. Two NLP systems, BioMedLEE and MedLEE, were applied to Medline articles and discharge summaries, respectively. Disease and drug entities were identified using the ...
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    17. Déjà vu--a study of duplicate citations in Medline.

      Related Articles Déjà vu--a study of duplicate citations in Medline. Bioinformatics. 2008 Jan 15;24(2):243-9 Authors: Errami M, Hicks JM, Fisher W, Trusty D, Wren JD, Long TC, Garner HR MOTIVATION: Duplicate publication impacts the quality of the scientific corpus, has been difficult to detect, and studies this far have been limited in scope and size. Using text similarity searches, we were able to identify signatures of duplicate citations among a body of abstracts. RESULTS: A sample of 62,213 Medline citations was examined and a database of manually verified duplicate citations was created to study author ...
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    18. Enabling integrative genomic analysis of high-impact human diseases through text mining.

      Related Articles Enabling integrative genomic analysis of high-impact human diseases through text mining. Pac Symp Biocomput. 2008;:580-91 Authors: Dudley J, Butte AJ Our limited ability to perform large-scale translational discovery and analysis of disease characterizations from public genomic data repositories remains a major bottleneck in efforts to translate genomics experiments to medicine. Through comprehensive, integrative genomic analysis of all available human disease characterizations we gain crucial insight into the molecular phenomena underlying pathogenesis as well as intra- and inter-disease differentiation. Such knowledge is crucial in the development of improved clinical diagnostics and the identification of molecular targets for novel ...
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    19. Assisted curation: does text mining really help?

      Related Articles Assisted curation: does text mining really help? Pac Symp Biocomput. 2008;:556-67 Authors: Alex B, Grover C, Haddow B, Kabadjov M, Klein E, Matthews M, Roebuck S, Tobin R, Wang X Although text mining shows considerable promise as a tool for supporting the curation of biomedical text, there is little concrete evidence as to its effectiveness. We report on three experiments measuring the extent to which curation can be speeded up with assistance from Natural Language Processing (NLP), together with subjective feedback from curators on the usability of a curation tool that integrates NLP hypotheses for protein-protein interactions ...
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    20. Filling the gaps between tools and users: a tool comparator, using protein-protein interaction as an example.

      Related Articles Filling the gaps between tools and users: a tool comparator, using protein-protein interaction as an example. Pac Symp Biocomput. 2008;:616-27 Authors: Kano Y, Nguyen N, Saetre R, Yoshida K, Miyao Y, Tsuruoka Y, Matsubayashi Y, Ananiadou S, Tsujii J Recently, several text mining programs have reached a near-practical level of performance. Some systems are already being used by biologists and database curators. However, it has also been recognized that current Natural Language Processing (NLP) and Text Mining (TM) technology is not easy to deploy, since research groups tend to develop systems that cater specifically to their own ...
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    21. The strength of co-authorship in gene name disambiguation.

      Related Articles The strength of co-authorship in gene name disambiguation. BMC Bioinformatics. 2008 Jan 29;9(1):69 Authors: Farkas R ABSTRACT: BACKGROUND: A biomedical entity mention in articles and other free texts is often ambiguous. For example, 13% of the gene names (aliases) might refer to more than one gene. The task of Gene Symbol Disambiguation (GSD) - a special case of Word Sense Disambiguation (WSD) - is to assign a unique gene identifier for all identified gene name aliases in biology-related articles. Supervised and unsupervised machine learning WSD techniques have been applied in the biomedical field with promising results. We ...
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    22. Representing default knowledge in biomedical ontologies: application to the integration of anatomy and phenotype ontologies.

      Related Articles Representing default knowledge in biomedical ontologies: application to the integration of anatomy and phenotype ontologies. BMC Bioinformatics. 2007;8:377 Authors: Hoehndorf R, Loebe F, Kelso J, Herre H BACKGROUND: Current efforts within the biomedical ontology community focus on achieving interoperability between various biomedical ontologies that cover a range of diverse domains. Achieving this interoperability will contribute to the creation of a rich knowledge base that can be used for querying, as well as generating and testing novel hypotheses. The OBO Foundry principles, as applied to a number of biomedical ontologies, are designed to facilitate this interoperability. However ...
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    23. Deafness mutation mining using regular expression based pattern matching.

      Related Articles Deafness mutation mining using regular expression based pattern matching. BMC Med Inform Decis Mak. 2007;7:32 Authors: Frenz CM BACKGROUND: While keyword based queries of databases such as Pubmed are frequently of great utility, the ability to use regular expressions in place of a keyword can often improve the results output by such databases. Regular expressions can allow for the identification of element types that cannot be readily specified by a single keyword and can allow for different words with similar character sequences to be distinguished. RESULTS: A Perl based utility was developed to allow the use ...
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      Discourse, Entailment, Machine Translation, NER, Parsing, Segmentation, Semantic, Sentiment, Summarization, WSD