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PubMed1992

Field-testing the new DECtalk PC system for medical applications.

Synthesized human speech has now reached a new level of performance. With the introduction of DEC's new DECtalk PC, the small system developer will have a very powerful tool for creative design. It has been our privilege to be involved in the beta-testing of this new device and to add a medical dictionary which covers a wide range of medical terminology. With the inherent board level understanding of speech synthesis and the medical dictionary, it is now possible to provide full digital speech output for all medical files and terms. The application of these tools will cover a wide range of options for the future and allow a new dimension in dealing with the complex user interface experienced in medical practice.

Artificial Intelligence↗
PubMed1984

Vascular surgical data registries for small computers.

Recent designs for computer-based vascular surgical registries and clinical data bases have employed large centralized systems with formal programming and mass storage. Small computers, of the types created for office use or for word processing, now contain sufficient speed and memory storage capacity to allow construction of decentralized office-based registries. Using a standardized dictionary of terms and a method of data organization adapted to word processing, we have created a new vascular surgery data registry, "VASREG." Data files are organized without programming, and a limited number of powerful logical statements in English are used for sorting. The capacity is 25,000 records with current inexpensive memory technology. VASREG is adaptable to computers made by a variety of manufacturers, and interface programs are available for conversion of the word processor formated registry data into forms suitable for analysis by programs written in a standard programming language. This is a low-cost clinical data registry available to any physician. With a standardized dictionary, preparation of regional and national statistical summaries may be facilitated.

Computers↗
PubMed2004

Medication use during pregnancy: data from the Avon Longitudinal Study of Parents and Children.

OBJECTIVE: To present data on the self-reported use of all types of medicinal products collected during pregnancy in a large cohort in southwest England. METHODS: Pregnant women with a delivery date during 1991-1992 and forming part of the prospective, population-based Avon Longitudinal Study of Parents and Children (ALSPAC) were sent up to four self-completion postal questionnaires during pregnancy. Text data collected from the questions on drug usage were coded using an ALSPAC drug dictionary based on the World Health Organization Drug Dictionary. RESULTS: At least one antenatal self-completion questionnaire was completed for 14,119 pregnancies, and 11,545 women completed all four. The data included prescription, over-the-counter, herbal and homeopathic products as well as iron, vitamins and other supplements. Only 7.6% did not report use of any medicinal product throughout their entire pregnancy. The remaining 92.4% used at least one product at some stage. After exclusion of iron, folate, vitamins, supplements, herbal and homeopathic products and skin emollients, 83% of those completing all questionnaires had used conventional therapeutic drugs. Analgesics were reported by approximately one-third of women at each stage during pregnancy, and paracetamol was the most frequently reported substance. Iron preparations were reported by 33% of the full cohort, at some stage, and folate by 21.9%. Use of anti-anaemic products increased during pregnancy with the greatest incidence at 32 weeks. Other vitamins and supplements were taken by 17.4% at some stage. Use of vitamins decreased throughout pregnancy from 9.6% in early pregnancy to 5% at 32 weeks. Antacids were reported by 23% at 32 weeks. The reported incidence of antibiotic use decreased slightly during pregnancy from 8% early on to 5.8% at 32 weeks; amoxicillin was the most frequently reported antibacterial. CONCLUSION: Use of medicinal products was high during pregnancy in the ALSPAC cohort. This finding is consistent with data from recent publications.

Adolescent↗
PubMedDate not supplied

An internet-based "kinetic imaging system" (KIS) for MicroPET.

Many considerations, involving understanding and selection of multiple experimental parameters, are required to perform MicroPET studies properly. The large number of these parameters/variables and their complicated interdependence make their optimal choice nontrivial. We have a developed kinetic imaging system (KIS), an integrated software system, to assist the planning, design, and data analysis of MicroPET studies. The system serves multiple functions-education, virtual experimentation, experimental design, and image analysis of simulated/experimental data-and consists of four main functional modules--"Dictionary," "Virtual Experimentation," "Image Analysis," and "Model Fitting." The "Dictionary" module provides didactic information on tracer kinetics, pharmacokinetic, MicroPET imaging, and relevant biological/pharmacological information. The "Virtual Experimentation" module allows users to examine via computer simulations the effect of biochemical/pharmacokinetic parameters on tissue tracer kinetics. It generates dynamic MicroPET images based on the user's assignment of kinetics or kinetic parameters to different tissue organs in a 3-D digital mouse phantom. Experimental parameters can be adjusted to investigate the design options of a MicroPET experiment. The "Image Analysis" module is a full-fledged image display/manipulation program. The "Model Fitting" module provides model-fitting capability for measured/simulated tissue kinetics. The system can be run either through the Web or as a stand-alone process. With KIS, radiotracer characteristics, administration method, dose level, imaging sequence, and image resolution-to-noise tradeoff can be evaluated using virtual experimentation. KIS is designed for biology/pharmaceutical scientists to make learning and applying tracer kinetics fun and easy.

Animals↗
PubMed2007

A matching pursuit-based signal complexity measure for the analysis of newborn EEG.

This paper presents a new relative measure of signal complexity, referred to here as relative structural complexity (RSC), which is based on the matching pursuit (MP) decomposition. By relative, we refer to the fact that this new measure is highly dependent on the decomposition dictionary used by MP. The structural part of the definition points to the fact that this new measure is related to the structure, or composition, of the signal under analysis. After a formal definition, the proposed RSC measure is used in the analysis of newborn electroencephalogram (EEG). To do this, firstly, a time-frequency decomposition dictionary is specifically designed to compactly represent the newborn EEG seizure state using MP. We then show, through the analysis of synthetic and real newborn EEG data, that the relative structural complexity measure can indicate changes in EEG structure as it transitions between the two EEG states; namely seizure and background (non-seizure).

Algorithms↗
PubMed1991

Introduction to special issue of Cognition on lexical and conceptual semantics.

It is the fate of those who dwell at the lower employments of life, to be rather driven by the fear of evil, than attracted by the prospect of good; to be exposed to censure, without hope of praise; to be disgraced by miscarriage, or punished for neglect, where success would have been without applause, and diligence without reward. Among these unhappy mortals is the writer of dictionaries ... (Preface, Samuel Johnson's Dictionary, 1755).

Cognition↗
PubMed1978

The perceptual use of semantic rules by normal-hearing and hard-of-hearing children.

This study investigated the effects of varying degrees of linguistic constraint upon the performance of hard-of-hearing subjects in a repetition task. Experimental stimuli consisted of three sets of sentence strings: grammatical, semantically anomalous, and ungrammatical, respectively. While the control group performed essentially equally across all three conditions, the hard-of-hearing group performed best to the grammatical stimuli and worst to the ungrammatical stimuli. It was hypothesized that the hard-of-hearing subjects employed a primitive sentence dictionary, while the normal-hearing subjects had developed a more sophisticated word dictionary.

Adolescent↗
PubMed1994

Word skills of children normal and impaired in communication skills and measures of language and speech development.

Results from two related investigations are reported, one using 60 normal language learners, ages 3-5 and one using 34 children with communication disorders, ages 5.4-8.5. Tasks involving the sequential recall of words from five categories (nouns, verbs, adjectives, adverbs, and prepositions) were given to the subjects in each investigation, thus providing an opportunity to compare group performances. A hierarchy of recall strengths of words from different categories and the organizational pattern of scores was determined for each group. Each group's word category scores were used as independent variables in regression analyses to predict scores from a battery of language tests and a test of phonology. The results were anticipated to be capable of contributing to descriptions of children's mental dictionaries, have implications for word category differences in normal and impaired language learners, and clinical relevance. Comparisons of the word recall accuracy of skills of children from each group revealed that the younger normal Ss had word scores equal to the older language and speech impaired children. However, the hierarchy of word category strengths and the patterns of organization within each group's mental dictionary were essentially the same in both groups. Word category scores predicted language and speech scores in both investigations, but the prediction was stronger in the children having impaired language or speech.

Child↗
PubMed1991

A comparison of the late radiation changes after three schedules of radiotherapy.

The late radiation change observed in 15 patients treated for carcinoma of oral cavity or oropharynx using continuous hyperfractionated accelerated radiotherapy (CHART) was compared to that seen in 15 similar patients treated with conventional radiotherapy. The average follow up was, 31 and 33 months, respectively. A new dictionary for the recording of radiation morbidity, developed in our centre, was employed and proved highly satisfactory in the recording of the changes observed in these patients and also in a third group treated by a combination of chemotherapy and hypofractionated radiotherapy in hyperbaric oxygen. The dictionary was able to record all the morbidity clinically seen with these three treatment schemes. The late changes observed in skin and mucosa with CHART were similar to those observed with conventional radiotherapy, but hair regrowth was observed in six out of 10 men treated with CHART compared with persistent, partial or complete hair loss in all nine men treated with the conventional scheme; after CHART there was also a trend towards less taste impairment and less severe dryness of mouth.

Adult↗
PubMed1981

A pain vocabulary in Finnish-The Finnish pain questionnaire.

Words related to pain were collected by asking 59 students and 18 patients to create a list by free association. Each subject was then given a dictionary-derived Finnish version of the McGill Pain Questionnaire (MPQ) with the words arranged in alphabetical order and was asked to place his own words among the dictionary-derive words which appeared most appropriate. Simultaneously, each word was allocated on a visual analogue scale (VAS) in order of increasing intensity. A vocabulary using the MPQ groups was then collated using the words for which at least one-half of the subjects agreed as to classification. The words in each group were presented in alphabetical order. The list was then given to 76 university students whose job was to decide if in fact each word did belong to the class assigned. Following this, the words were arranged on a VAS scale in intensity order. The words mm-mean differences were then compared using a t-test. Those words were chosen for the pain vocabulary which reflected a statistically significant intensity change and were most often to be found in the word-list. The same method is applicable irrespective of language. Words are replaceable by numerical values so that follow-up and renewed investigations become statistically comparable.

Finland↗
PubMed2004

iProLINK: an integrated protein resource for literature mining.

The exponential growth of large-scale molecular sequence data and of the PubMed scientific literature has prompted active research in biological literature mining and information extraction to facilitate genome/proteome annotation and improve the quality of biological databases. Motivated by the promise of text mining methodologies, but at the same time, the lack of adequate curated data for training and benchmarking, the Protein Information Resource (PIR) has developed a resource for protein literature mining--iProLINK (integrated Protein Literature INformation and Knowledge). As PIR focuses its effort on the curation of the UniProt protein sequence database, the goal of iProLINK is to provide curated data sources that can be utilized for text mining research in the areas of bibliography mapping, annotation extraction, protein named entity recognition, and protein ontology development. The data sources for bibliography mapping and annotation extraction include mapped citations (PubMed ID to protein entry and feature line mapping) and annotation-tagged literature corpora. The latter includes several hundred abstracts and full-text articles tagged with experimentally validated post-translational modifications (PTMs) annotated in the PIR protein sequence database. The data sources for entity recognition and ontology development include a protein name dictionary, word token dictionaries, protein name-tagged literature corpora along with tagging guidelines, as well as a protein ontology based on PIRSF protein family names. iProLINK is freely accessible at http://pir.georgetown.edu/iprolink, with hypertext links for all downloadable files.

Computational Biology↗
PubMed2004

A simple error classification system for understanding sources of error in automatic speech recognition and human transcription.

OBJECTIVES: To (1) discover the types of errors most commonly found in clinical notes that are generated either using automatic speech recognition (ASR) or via human transcription and (2) to develop efficient rules for classifying these errors based on the categories found in (1). The purpose of classifying errors into categories is to understand the underlying processes that generate these errors, so that measures can be taken to improve these processes. METHODS: We integrated the Dragon NaturallySpeaking v4.0 speech recognition engine into the Regenstrief Medical Record System. We captured the text output of the speech engine prior to error correction by the speaker. We also acquired a set of human transcribed but uncorrected notes for comparison. We then attempted to error correct these notes based on looking at the context alone. Initially, three domain experts independently examined 104 ASR notes (containing 29,144 words) generated by a single speaker and 44 human transcribed notes (containing 14,199 words) generated by multiple speakers for errors. Collaborative group sessions were subsequently held where error categorizes were determined and rules developed and incrementally refined for systematically examining the notes and classifying errors. RESULTS: We found that the errors could be classified into nine categories: (1) announciation errors occurring due to speaker mispronounciation, (2) dictionary errors resulting from missing terms, (3) suffix errors caused by misrecognition of appropriate tenses of a word, (4) added words, (5) deleted words, (6) homonym errors resulting from substitution of a phonetically identical word, (7) spelling errors, (8) nonsense errors, words/phrases whose meaning could not be appreciated by examining just the context, and (9) critical errors, words/phrases where a reader of a note could potentially misunderstand the concept that was related by the speaker. CONCLUSIONS: A simple method is presented for examining errors in transcribed documents and classifying these errors into meaningful and useful categories. Such a classification can potentially help pinpoint sources of such errors so that measures (such as better training of the speaker and improved dictionary and language modeling) can be taken to optimize the error rates.

Automation↗
PubMed2001

META V. A model of photodegradation for the prediction of photoproducts of chemicals under natural-like conditions.

Our goal was to create a photodegradation model based on the META expert system [G. Klopman, M. Dimayuga, J. Talafous, J. Chem. Inf. Comput. Sci. 34 (1994a) 1320-1325]. This requires the development of a dictionary of photodegradation pathways. Equipped with such a dictionary, we found that META successfully predicts degradation pathways of organic compounds under UV light. Our model was tested on a wide range of industrial compounds for which literature data exists. The results were excellent as the hit/miss ratio was better than 92%. This work complements our previous elaboration of equivalent mammal metabolism, aerobic and anaerobic biodegradation models.

Air Pollutants↗
PubMed2003

The method to compare nucleotide sequences based on the minimum entropy principle.

A new method to compare two (or several) symbol sequences is developed. The method is based on the comparison of the frequencies of the small fragments of the compared sequences; it requires neither string editing, nor other transformations of the compared objects. The comparison is executed through a calculation of the specific entropy of a frequency dictionary against the special dictionary called the hybrid one; this latter is the statistical ancestor of the group of sequences under comparison. Some applications of the developed method in the fields of genetics and bioinformatics are discussed.

Animals↗
PubMed2000

Internet-based decision-support server for acute abdominal pain.

The paper describes conception and prototypical design of a decision-support server for acute abdominal pain. Existing formal methods to develop and exchange scores, guidelines and algorithms are used for integration. For scoring systems a work-up to separate terminological information from structure is described. The terminology is separately stored in a data dictionary and the structure in a knowledge base. This procedure enables a reuse of terminology for documentation and decision-support. The whole system covers a decision-support server written in C++ with underlying data dictionary and knowledge base, a documentation module written in Java and a CORBA middleware that establishes a connection via Internet.

Abdominal Pain↗
PubMed2001

Decision support for infectious diseases--a working prototype.

This paper presents a decision support system for nosocomial infections and its integration in the large HIS of the University Hospital of Giessen. The system comprises five different engines and a data dictionary. It is designed to detect hospital acquired infections even in a situation where only a restricted amount of clinical data is available (the data is split up in different information systems). Furthermore the model prevents time consuming manual data entry. The five engines split the main task into: (1) a preselection, which sorts out patients who definitely do not have a nosocomial infection; (2) a rule based reasoning process which detects patients likely to have such an infection; (3) an alarm process which is responsible for the presentation of the alert; (4) an explanation process to follow up the reasoning; and (5) statistic tools to answer specific hygienic questions. A data dictionary supplies the controlled vocabulary, which is required to understand data structures used in the different clinical subsystems and may those with each other.

Artificial Intelligence↗
PubMed1990

CHEMLEARN: microcomputer-based training for CHEMLINE, an alternative to formal classroom training.

CHEMLINE (CHEMical Dictionary OnLINE), the National Library of Medicine's online chemical dictionary file, is primarily used by librarians and information scientists to enhance the retrieval of bibliographic information associated with chemical substances. This paper will discuss CHEMLEARN, a microcomputer-based training program designed to provide inexpensive, easily accessible self-instruction as an alternative to formal classroom training in the use of CHEMLINE. CHEMLEARN allows novice users to learn at their own pace and with considerable program feedback. In addition, it provides the skilled searcher with a way to reinforce or recall previously learned search techniques without incurring online charges. CHEMLEARN may be used in place of formal training or as a precursor to or a refresher following formal training.

Chemical Phenomena↗
PubMed1975

Data compression of large document data bases.

Consideration is given to a document data base that is structured for information retrieval purposes by means of an inverted index and term dictionary. Vocabulary characteristics of various fields are described, and it is shown how the data base may be stored in a compressed form by use of restricted variable length codes that produce a compression not greatly in excess of the optimum that could be achieved through use of Huffman codes. The coding is word oriented. An alternative scheme of word fragment coding is described. It has the advantage that it allows the use of a small dictionary, but is less efficient with respect to compression of the data base.

Computers↗