SEARCH · Search PubMed

Results for “Textual analysis”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13Linked to original sources

PubMed1994

Natural language processing of medical texts within the HELIOS environment.

A large number of hospital applications are potentially interested in natural language processing since they currently heavily depend on an efficient use of a huge amount of textual information. The need for systems that are able to accept multiple European languages is of paramount interest, as language barriers can be a strong impediment for large-scale communication in Europe, in particular regarding telemedicine. In the context of the AIM project HELIOS, the Natural Language Processing (NLP) component offers a large variety of medical services according to natural language free input. It allows the multilingual analysis of medical texts (currently in English, French and German) and the storage of the meaning of these texts under a deep knowledge representation that can be queried whenever it is needed. In addition, it provides facilities to handle knowledge source embedded into the conceptual typologies and into the dictionaries. This article aims at describing all these functionalities and their integration into the environment of the HELIOS project.

Artificial Intelligence↗

PubMed2004

PlasMapper: a web server for drawing and auto-annotating plasmid maps.

PlasMapper is a comprehensive web server that automatically generates and annotates high-quality circular plasmid maps. Taking only the plasmid/vector DNA sequence as input, PlasMapper uses sequence pattern matching and BLAST alignment to automatically identify and label common promoters, terminators, cloning sites, restriction sites, reporter genes, affinity tags, selectable marker genes, replication origins and open reading frames. PlasMapper then presents the identified features in textual form and as high-resolution, multicolored graphical output. The appearance and contents of the output can be customized in numerous ways using several supplied options. Further, PlasMapper images can be rendered in both rasterized (PNG and JPG) and vector graphics (SVG) formats to accommodate a variety of user needs or preferences. The images and textual output are of sufficient quality that they may be used directly in publications or presentations. The PlasMapper web server is freely accessible at http://wishart.biology.ualberta.ca/PlasMapper.

Chromosome Mapping↗

PubMed1990

Computerized medical records: the need for a standard.

Major concepts introduced in this paper are as follows. 1) Organization, with its attendant qualities of accuracy, consistency, legibility, completeness, and simplicity, is the heart of the medical record. Technology should not be allowed to obscure this goal. 2) The main function of the computerized medical record is data storage with the qualities of organization noted above. This function must be clearly separated from condensation, analysis, or other secondary manipulation of data. 3) Many aspects of data manipulation call for the judgment of a physician. This judgement may be aided by computer software, but not replaced by it. 4) Present technological barriers, most notably speed, permanent large storage, and voice input should not influence the design of the effective computerized record. Future technology will be able to service the carefully designed medical record. 5) Textual parts of the computerized medical record can follow a simple and machine independent outline format. All parts of the record should use a textual introduction emphasizing patient and record identification. 6) A patient profile is central to each patient file. Updating this profile as needed must be recognized as a primary function of the physician at every patient encounter. 7) Acceptance of a standard for the computerized medical record now, before technology has matured and software diversified, will avoid a pitfall commonly experienced in other fields and save substantial healthcare funds. This standard should be geared to the needs of physicians and patients, not to the constraints of technology. The future of medical computing is bright. Obstacles to the practical use of the computerized medical record exist, but we may expect these to vanish within a few years. The great challenge to physicians now is to take this opportunity to control a new technology, rather than to be driven by it. The soul of good medicine is not in the equipment available, but in the rational and carefully thoughtout use of those tools at hand. We must recognize now the need for a uniform style of computerized medical record before the technological establishment besieges us with a flood of specialized, non-interchangeable, and expensive machines. Indeed, a bit of careful thought now as the foundation is laid can prevent the tangled confusion so typical of new technology. We have a golden opportunity to avoid a new round of escalating medical costs.

Data Display↗

PubMed1995

An overview of statistical methods for the classification and retrieval of patient events.

Statistical methods that can support text retrieval are becoming an increasing focus of medical informatics activities. We overview our adaptation of existing knowledge sources to create pseudo-documents for concept based latent semantic indexing. Experience demonstrated this tack of limited practical value, since retrieval performance was invariably unsatisfactory. We discovered this was due in part to the introduction of a vocabulary gap between the queries and the cases we sought to retrieve. In part to address this problem, and to avail our large body of humanly coded text as a knowledge source, we developed a least squares fit alternative for the computer assisted indexing and retrieval of biomedical texts. This technique demonstrates equivalent or superior retrieval performance when compared to all other textual retrieval techniques. It does not depend upon elaborate knowledge bases, lexicons, or thesauri. It is a promising technique for classifying and retrieving the large volumes of clinical text.

Abstracting and Indexing↗

PubMed2003

Applying the SOM model to text classification according to register and stylistic content.

We report on the application of the Self-Organizing Map (SOM) classification method to the task of categorizing texts according to their register and the style of their author. The SOM has been selected as its performance in various data-mining applications has been found to be highly successful. Here, the method is evaluated against the task of clustering textual data which are corpora of texts written in the Greek language; the parameters used depict linguistically important structural properties of the texts. The experiments reported indicate that the SOM results are equivalent to those generated by statistical methods.

Algorithms↗

PubMed1997

PowerBLAST: a new network BLAST application for interactive or automated sequence analysis and annotation.

As the rate of DNA sequencing increases, analysis by sequence similarity search will need to become much more efficient in terms of sensitivity, specificity, automation potential, and consistency in annotation. PowerBLAST was developed, in part, to address these problems. PowerBLAST includes a number of options for masking repetitive elements and low complexity subsequences. It also has the capacity to restrict the search to any level of NCBI's taxonomy index, thus supporting "comparative genomics" applications. Postprocessing of the BLAST output using the SIM series of algorithms produces optimal, gapped alignments, and multiple alignments when a region of the query sequence matches multiple database sequences. PowerBLAST is capable of processing sequences of any length because it divides long query sequences into overlapping fragments and then merges the results after searching. The results may be viewed graphically, as a textual representation, or as an HTML page with links to GenBank and Entrez. For matching database sequences, annotated features are superimposed on the aligned query sequence in the output, thus greatly increasing the ease of interpretation. Such features may be used for automated annotation of new sequence because PowerBLAST output in ASN.1 form may be "dragged and dropped" into NCBI's Sequin program for sequence annotation and submission. PowerBLAST is capable of analyzing and annotating a 100-kb query in 60 min on NCBI's BLAST server.

Amino Acid Sequence↗

PubMed1998

BioViews: Java-based tools for genomic data visualization.

Visualization tools for bioinformatics ideally should provide universal access to the most current data in an interactive and intuitive graphical user interface. Since the introduction of Java, a language designed for distributed programming over the Web, the technology now exists to build a genomic data visualization tool that meets these requirements. Using Java we have developed a prototype genome browser applet (BioViews) that incorporates a three-level graphical view of genomic data: a physical map, an annotated sequence map, and a DNA sequence display. Annotated biological features are displayed on the physical and sequence-based maps, and the different views are interconnected. The applet is linked to several databases and can retrieve features and display hyperlinked textual data on selected features. In addition to browsing genomic data, different types of analyses can be performed interactively and the results of these analyses visualized alongside prior annotations. Our genome browser is built on top of extensible, reusable graphic components specifically designed for bioinformatics. Other groups can (and do) reuse this work in various ways. Genome centers can reuse large parts of the genome browser with minor modifications, bioinformatics groups working on sequence analysis can reuse components to build front ends for analysis programs, and biology laboratories can reuse components to publish results as dynamic Web documents.

Animals↗

PubMed2005

A controlled trial of automated classification of negation from clinical notes.

BACKGROUND: Identification of negation in electronic health records is essential if we are to understand the computable meaning of the records: Our objective is to compare the accuracy of an automated mechanism for assignment of Negation to clinical concepts within a compositional expression with Human Assigned Negation. Also to perform a failure analysis to identify the causes of poorly identified negation (i.e. Missed Conceptual Representation, Inaccurate Conceptual Representation, Missed Negation, Inaccurate identification of Negation). METHODS: 41 Clinical Documents (Medical Evaluations; sometimes outside of Mayo these are referred to as History and Physical Examinations) were parsed using the Mayo Vocabulary Server Parsing Engine. SNOMED-C was used to provide concept coverage for the clinical concepts in the record. These records resulted in identification of Concepts and textual clues to Negation. These records were reviewed by an independent medical terminologist, and the results were tallied in a spreadsheet. Where questions on the review arose Internal Medicine Faculty were employed to make a final determination. RESULTS: SNOMED-CT was used to provide concept coverage of the 14,792 Concepts in 41 Health Records from John's Hopkins University. Of these, 1,823 Concepts were identified as negative by Human review. The sensitivity (Recall) of the assignment of negation was 97.2% (p < 0.001, Pearson Chi-Square test; when compared to a coin flip). The specificity of assignment of negation was 98.8%. The positive likelihood ratio of the negation was 81. The positive predictive value (Precision) was 91.2% CONCLUSION: Automated assignment of negation to concepts identified in health records based on review of the text is feasible and practical. Lexical assignment of negation is a good test of true Negativity as judged by the high sensitivity, specificity and positive likelihood ratio of the test. SNOMED-CT had overall coverage of 88.7% of the concepts being negated.

Abstracting and Indexing↗

PubMed1990

Effects of textual cue manipulation on student recall in an information mapped nutrition text.

Using the subject area of nutrition, this study examined the effects of different instructional features of an adjunctive text for nursing students who varied in reading level. Specifically, the study investigated the effects of both variations in instructional features of information-mapped text and the differences in student reading levels on immediate recall scores and work time spent on the modules. A sample of 65 nursing students was classified into high and low reading groups according to the Nelson-Denny Reading Test, then randomly assigned to one of the three treatment groups. Analysis of covariance indicated significant treatment effects after adjusting the recall scores for the influence of verbal aptitude. Information-mapped text with either postquestions or postquestions and feedback yielded higher recall scores than information-mapped text alone. Subjects whose modules contained postquestions or postquestions and feedback spent significantly more work time than subjects whose modules did not contain those features; however, when the recall scores were adjusted for the influence of work time spent on the modules, there were no significant differences. Conclusions and recommendations for the text construction process, especially for the adjunctive nursing text, are presented.

Adult↗

PubMed1977

Intonation in discourse analysis. With material from Finnish, English, Alemannic German.

ARGUMENT: intonation is not additional, but essential to the composition of texts. MOTIVATION: even pathological (written) texts can be made to sound normal when read with a good intonation; even well-formed (written) texts cannot be put across when read with a poor intonation; loss of intonation, in aphasia, is coupled with inability to handle texts, and inversely. THEORY: intonation is analysed either as phonological pattern or as a constituent of texts. The lexical meaning of intonations (such as question, statement) is spurious; social tradition makes available certain (spoken) rhetorical topoi for use in standard situations; their use ensures textual meaning. It is not predictable in any given instance.

England↗

PubMed2006

Study of physiological responses to acute carbon monoxide exposure with a human patient simulator.

Human patient simulators are widely used to train health professionals and students in a clinical setting, but they also can be used to enhance physiology education in a laboratory setting. Our course incorporates the human patient simulator for experiential learning in which undergraduate university juniors and seniors are instructed to design, conduct, and present (orally and in written form) their project testing physiological adaptation to an extreme environment. This article is a student report on the physiological response to acute carbon monoxide exposure in a simulated healthy adult male and a coal miner and represents how 1) human patient simulators can be used in a nonclinical way for experiential hypothesis testing; 2) students can transition from traditional textbook learning to practical application of their knowledge; and 3) student-initiated group investigation drives critical thought. While the course instructors remain available for consultation throughout the project, the relatively unstructured framework of the assignment drives the students to create an experiment independently, troubleshoot problems, and interpret the results. The only stipulation of the project is that the students must generate an experiment that is physiologically realistic and that requires them to search out and incorporate appropriate data from primary scientific literature. In this context, the human patient simulator is a viable educational tool for teaching integrative physiology in a laboratory environment by bridging textual information with experiential investigation.

Adaptation, Physiological↗

PubMed2005

Communicating quality of life information to cancer patients: a study of six presentation formats.

PURPOSE: To determine which formats for presenting health-related quality of life (HRQL) data are interpreted most accurately and are most preferred by cancer patients. Patients often want a great deal of information about cancer treatments, including information relevant to HRQL. Clinical trials provide methodologically sound HRQL data that may be useful to patients. PATIENTS AND METHODS: In a multicenter study, 198 patients with previously treated cancer participated in a structured interview. Participants judged HRQL information presented in one textual and five graphical formats. Outcome measures included the accuracy of patients' interpretations and ease-of-use and helpfulness ratings for each format. RESULTS: Correct interpretations ranged from 85% to 98% across formats (F = 10.3, P < .0001) with line graphs of mean HRQL scores over time being interpreted correctly most often. Older patients and less-educated patients were less likely to interpret graphs accurately (F = 7.3, P = .008; and F = 10.6, P = .001, respectively), but all groups were most accurate on simple line graphs. Multivariate analysis revealed that format type, participant age and education were independent predictors of accuracy rates. Patients' ratings also varied across formats both for ease of understanding scores (F = 12.1, P < .0001) and for helpfulness scores (F = 13.2, P < .0001), with line graphs being rated highest on both outcomes. CONCLUSION: Patients generally prefer a simple linear representation of group mean HRQL scores, and can accurately interpret data presented in this format more than 98% of the time irrespective of their age group and educational level. The findings have important implications for the communication of clinical trial HRQL results.

Aged↗

PubMedDate not supplied

Automating data collection, analysis & documentation for medical research.

The personal computer (PC) has evolved into a powerful, cost-effective computing platform capable of performing many tasks associated with the management of scientific, clinical, or other information. These activities include: Control of an instrument by the PC; Data acquisition from an experiment or subject; Analysis of the data that the computer has collected; Presentation of the analyzed data in a form that makes it useful; Long term storage of data. Until recently, these tasks required the user to be familiar with a high level programming language (HLL) in order to fulfill these assignments. Arcane text based programs whose logic is often difficult to follow is gradually being replaced by visual programming using a terminology based on icons where ideas familiar to scientists and medical practitioners rely on graphic symbols rather than textual language to describe programming actions.

Microcomputers↗

PubMed1998

SEView: a Java applet for browsing molecular sequence data.

SEView is a Java applet that represents known or predicted elements of a protein or nucleotide sequence. It replaces or supplements the textual format of databases or program output with an interactive, graphical representation that is easily available through a WWW browser. Independence from the source data's format is achieved through a description language and ad hoc translators, which make the system versatile and flexible.

Computer Graphics↗

PubMed2006

Readability of pediatric health materials for preventive dental care.

BACKGROUND: This study examined the content and general readability of pediatric oral health education materials for parents of young children. METHODS: Twenty-seven pediatric oral health pamphlets or brochures from commercial, government, industry, and private nonprofit sources were analyzed for general readability ("usability") according to several parameters: readability, (Flesch-Kincaid grade level, Flesch Reading Ease, and SMOG grade level); thoroughness, (inclusion of topics important to young childrens' oral health); textual framework (frequency of complex phrases, use of pictures, diagrams, and bulleted text within materials); and terminology (frequency of difficult words and dental jargon). RESULTS: Readability of the written texts ranged from 2nd to 9th grade. The average Flesch-Kincaid grade level for government publications was equivalent to a grade 4 reading level (4.73, range, 2.4-6.6); F-K grade levels for commercial publications averaged 8.1 (range, 6.9-8.9); and industry published materials read at an average Flesch-Kincaid grade level of 7.4 (range, 4.7-9.3). SMOG readability analysis, based on a count of polysyllabic words, consistently rated materials 2 to 3 grade levels higher than did the Flesch-Kincaid analysis. Government sources were significantly lower compared to commercial and industry sources for Flesch-Kincaid grade level and SMOG readability analysis. Content analysis found materials from commercial and industry sources more complex than government-sponsored publications, whereas commercial sources were more thorough in coverage of pediatric oral health topics. Different materials frequently contained conflicting information. CONCLUSION: Pediatric oral health care materials are readily available, yet their quality and readability vary widely. In general, government publications are more readable than their commercial and industry counterparts. The criteria for usability and results of the analyses presented in this article can be used by consumers of dental educational materials to ensure that their choices are well-suited to their specific patient population.

Journal Article↗

PubMed2000

[Information and retrieval diagnostic system for inherited metabolic diseases].

The paper analyzes a procedure for construction and practical use of an information and retrieval diagnostic system (IRDS) for inherited metabolic diseases (IMD) in the context of an automatic working place for consulting genetics. An IRDS structure for IMD is proposed, which involves the following functional elements: 1) a genetic register; 2) an inherited metabolic disease database (IMDD); 3) a special module for searching for the probable range of diagnoses; 4) an archive; 5) a special model for statistical analysis of the clinical polymorphism of IMD. The full insight into each nosological entity (n = 316) as part of IMD IRDS is gained by using a set of catalogues, such as a catalogue IMD classes (n = 22), that of IMD clinical symptoms and signs (n = 1215); that of IMD biochemical markers (n = 934); a list of all symptoms and signs for each nosological entity; that of major diagnostic signs for each nosological entity. The clinical picture is described within the framework of the unified structure that includes the following set of items: the textual description of the clinical picture of a disease in terms of major diagnostic signs, etiology, genetics, pathogenesis, a biochemical phenotype, paraclinical studies, differential diagnosis, treatment, and prevention. The system is provided with a simple and user-friendly interface that allows a user to have a prompt look at the data pertaining to each nosological entity, to find required references by employing multiple keys of data search, sort, and printing.

Diagnosis, Computer-Assisted↗

PubMedDate not supplied

Cardiovascular monitoring in the medical intensive care unit.

The need for and development of computer-based monitoring in medical intensive care are discussed. The critical care ward system at the University of Southern California's Center for the Critically Ill is described. Basic monitoring routines include measurement of heart rate; arterial, venous, and pulmonary pressures; core and peripheral temperature; and urine output. Other application programs handle cardiac output determinations, laboratory tests, narrative data entry, and process control. Data retrieval provides for tabular, textual, and graphic displays both at the bedside and in hard copy, as well as data printouts for research purposes. Computer control covers the vascular interface, automated pressure calibration, peristaltic pumps for fluid infusion and blood sampling, and urine collection and disposal. Using automated fluid challenge as a prototype, servo operations should be extended to mechanical ventilation and fluid therapy.

Blood Chemical Analysis↗

PubMed2004

Local backbone structure prediction of proteins.

A statistical analysis of the PDB structures has led us to define a new set of small 3D structural prototypes called Protein Blocks (PBs). This structural alphabet includes 16 PBs, each one is defined by the (phi, psi) dihedral angles of 5 consecutive residues. The amino acid distributions observed in sequence windows encompassing these PBs are used to predict by a Bayesian approach the local 3D structure of proteins from the sole knowledge of their sequences. LocPred is a software which allows the users to submit a protein sequence and performs a prediction in terms of PBs. The prediction results are given both textually and graphically.

Amino Acid Sequence↗