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PubMed2006

AIS 2005: a contemporary injury scale.

To determine and to quantify outcome from injury demands that multiple factors be universally applied so that there is uniform understanding that the same outcome is understood for the same injury. It is thus important to define the variables used in any outcome assessment. Critical to defining outcomes is the need for a universal language that defines individual injuries. The abbreviated injury scale (AIS) is the only dictionary specifically designed as a system to define the severity of injuries throughout the body. In addition to a universal injury language, it provides measures of injury severity that can be used to stratify and classify injury severity in all body regions. Its revision, AIS 2005 will be discussed here.

Abbreviated Injury Scale↗
PubMed2004

Using automatically learnt verb selectional preferences for classification of biomedical terms.

In this paper, we present an approach to term classification based on verb selectional patterns (VSPs), where such a pattern is defined as a set of semantic classes that could be used in combination with a given domain-specific verb. VSPs have been automatically learnt based on the information found in a corpus and an ontology in the biomedical domain. Prior to the learning phase, the corpus is terminologically processed: term recognition is performed by both looking up the dictionary of terms listed in the ontology and applying the C/NC-value method for on-the-fly term extraction. Subsequently, domain-specific verbs are automatically identified in the corpus based on the frequency of occurrence and the frequency of their co-occurrence with terms. VSPs are then learnt automatically for these verbs. Two machine learning approaches are presented. The first approach has been implemented as an iterative generalisation procedure based on a partial order relation induced by the domain-specific ontology. The second approach exploits the idea of genetic algorithms. Once the VSPs are acquired, they can be used to classify newly recognised terms co-occurring with domain-specific verbs. Given a term, the most frequently co-occurring domain-specific verb is selected. Its VSP is used to constrain the search space by focusing on potential classes of the given term. A nearest-neighbour approach is then applied to select a class from the constrained space of candidate classes. The most similar candidate class is predicted for the given term. The similarity measure used for this purpose combines contextual, lexical, and syntactic properties of terms.

Abstracting and Indexing↗
PubMed2005

Graph theoretic modeling of large-scale semantic networks.

During the past several years, social network analysis methods have been used to model many complex real-world phenomena, including social networks, transportation networks, and the Internet. Graph theoretic methods, based on an elegant representation of entities and relationships, have been used in computational biology to study biological networks; however they have not yet been adopted widely by the greater informatics community. The graphs produced are generally large, sparse, and complex, and share common global topological properties. In this review of research (1998-2005) on large-scale semantic networks, we used a tailored search strategy to identify articles involving both a graph theoretic perspective and semantic information. Thirty-one relevant articles were retrieved. The majority (28, 90.3%) involved an investigation of a real-world network. These included corpora, thesauri, dictionaries, large computer programs, biological neuronal networks, word association networks, and files on the Internet. Twenty-two of the 28 (78.6%) involved a graph comprised of words or phrases. Fifteen of the 28 (53.6%) mentioned evidence of small-world characteristics in the network investigated. Eleven (39.3%) reported a scale-free topology, which tends to have a similar appearance when examined at varying scales. The results of this review indicate that networks generated from natural language have topological properties common to other natural phenomena. It has not yet been determined whether artificial human-curated terminology systems in biomedicine share these properties. Large network analysis methods have potential application in a variety of areas of informatics, such as in development of controlled vocabularies and for characterizing a given domain.

Algorithms↗
PubMed2006

Automatic generation of spoken dialogue from medical plans and ontologies.

This paper presents some research undertaken as part of the EU-funded HOMEY project, into the application of intelligent dialogue systems to healthcare systems. The work presented here concentrates on the ways in which knowledge of underlying task structure (e.g., a medical guideline) can be combined with ontological knowledge (e.g., medical semantic dictionaries) to provide a basis for the automatic generation of flexible and re-configurable dialogue. This approach is next evaluated via a specific application that provides decision support to general practitioners to help determine whether or not a patient should be referred to a cancer specialist. The competence of the resulting dialogue application, its speech recognition performance, and dialogue performance are all evaluated to determine the applicability of this approach.

Artificial Intelligence↗
PubMed2006

Using MEDLINE as a knowledge source for disambiguating abbreviations and acronyms in full-text biomedical journal articles.

Biomedical abbreviations and acronyms are widely used in biomedical literature. Since many of them represent important content in biomedical literature, information retrieval and extraction benefits from identifying the meanings of those terms. On the other hand, many abbreviations and acronyms are ambiguous, it would be important to map them to their full forms, which ultimately represent the meanings of the abbreviations. In this study, we present a semi-supervised method that applies MEDLINE as a knowledge source for disambiguating abbreviations and acronyms in full-text biomedical journal articles. We first automatically generated from the MEDLINE abstracts a dictionary of abbreviation-full pairs based on a rule-based system that maps abbreviations to full forms when full forms are defined in the abstracts. We then trained on the MEDLINE abstracts and predicted the full forms of abbreviations in full-text journal articles by applying supervised machine-learning algorithms in a semi-supervised fashion. We report up to 92% prediction precision and up to 91% coverage.

Artificial Intelligence↗
PubMed2006

A principal calling: professionalism and health care services.

UNLABELLED: As heath care professionals, our "product" is clinical service. We demonstrate professionalism by attitudes, knowledge, and behaviors that reflect a multi-faceted approach to the standards, regulations, and principles underlying successful clinical practices. The issues facing practitioners who work in health care environments are complex, forming an infrastructure for conducting clinical and business operations. Issues discussed include: clinical quality and outcomes management; patient safety and medical errors; accreditation and compliance. A thorough knowledge of these topics forms the context within which we integrate our services with the larger health care community. In this age of accountability, inquiry, introspection and integrity are the keys to professionalism. LEARNING OUTCOMES: As a result of this activity, the reader will be able to: (1) discuss basic points related to the complex requirements and issues facing clinical practitioners today; (2) understand the components of "professional" practice within the health care community; (3) integrate quality management, regulatory compliance, and accreditation standards into every clinical practice. Profession: A calling requiring specialized knowledge and often long and intensive academic preparation; a principal calling, vocation, or employment. Professionalism: The conduct, aims, or qualities that characterize or mark a profession or professional person. -Webster's New Collegiate Dictionary.

Accreditation↗
PubMed2006

Antiulcer and in vitro antioxidant activities of Jasminum grandiflorum L.

The study was aimed at evaluating the antiulcer and antioxidant activities of 70% ethanolic axtract of leaves of Jasminum grandiflorum L. (JGLE). The leaves of Jasminum grandiflorum L. (Family: Oleaceae) is used in folk medicine for treating ulcerative stomatitis, skin diseases, ulcers, wounds, corns - a hard or soft hyperkeratosis of the sole of the human foot secondary to friction and pressure (Stedman's Medical Dictionary, 28th ed. Lippincott Williams & Wilkins, Philadelphia. p. 443), etc., Antiulcerogenic activity of JGLE (100 and 200 mg/kg, b.w., orally) was evaluated employing aspirin + pylorus ligation (APL) and alcohol (AL) induced acute gastric ulcer models and ulcer-healing activity using acetic acid-induced (AC) chronic ulcer model in rats. Both the antisecretory and cytoprotection hypothesis were evaluated. The antioxidant activity of JGLE has been assayed by using in vitro methods like 2,2-diphenyl-1-picrylhydrazylhydrate (DPPH) assay, reductive ability, superoxide anion scavenging activity, nitric oxide scavenging activity and total phenolic content, in order to explain the role of antioxidant principles in the antiulcerogenic activity of the extract. There was a significant (P<0.01) dose-dependent decrease in the ulcerative lesion index produced by all the three models in rats as compared to the standard drug famotidine (20 mg/kg, b.w. orally). The reduction in gastric fluid volume, total acidity and an increase in the pH of the gastric fluid in APL rats proved the antisecretory activity of JGLE. Additionally, JGLE completely healed the ulcer within 20 days of treatment in AC model as evidenced by histopathological studies. Like antiulcer activity, the free radical scavenging activities of JGLE depends on concentration and increased with increasing amount of the extract. These results suggest that leaves of Jasminum grandiflorum possess potential antiulcer activity, which may be attributed to its antioxidant mechanism of action.

Animals↗
PubMed2006

Structural diversity of domain superfamilies in the CATH database.

The CATH database of domain structures has been used to explore the structural variation of homologous domains in 294 well populated domain structure superfamilies, each containing at least three sequence diverse relatives. Our analyses confirm some previously detected trends relating sequence divergence to structural variation but for a much larger dataset and in some superfamilies the new data reveal exceptional structural variation. Use of a new algorithm (2DSEC) to analyse variability in secondary structure compositions across a superfamily sheds new light on how structures evolve. 2DSEC detects inserted secondary structures that embellish the core of conserved secondary structures found throughout the superfamily. Analysis showed that for 56% of highly populated superfamilies (>9 sequence diverse relatives), there are twofold or more increases in the numbers of secondary structures in some relatives. In some families fivefold increases occur, sometimes modifying the fold of the domain. Manual inspection of secondary structure insertions or embellishments in 48 particularly variable superfamilies revealed that although these insertions were usually discontiguous in the sequence they were often co-located in 3D resulting in a larger structural motif that often modified the geometry of the active site or the surface conformation promoting diverse domain partnerships and protein interactions. These observations, supported by automatic analysis of all well populated CATH families, suggest that accretion of small secondary structure insertions may provide a simple mechanism for evolving new functions in diverse relatives. Some layered domain architectures (e.g. mainly-beta and alpha-beta sandwiches) that recur highly in the genomes more frequently exploit these types of embellishments to modify function. In these architectures, aggregation occurs most often at the edges, top or bottom of the beta-sheets. Information on structural variability across domain superfamilies has been made available through the CATH Dictionary of Homologous Structures (DHS).

Amino Acid Sequence↗
PubMed2026

A Sentiment-Based Comparison of AI- and Physician-Generated Empathic Statements in Palliative Care.

CONTEXT: Empathic communication promotes trust in patient-provider relationships. As healthcare integrates artificial intelligence (AI) into patient communication, we have yet to understand how these models' communication compares to that of physicians. OBJECTIVES: Our primary objectives were to examine patient preferences for AI-generated vs. palliative care physician-generated empathic statements addressing fear and anxiety around cancer treatment, and to analyze associations between linguistic features and patient preferences. METHODS: We conducted a secondary analysis of the PALL-AI trial, a randomized controlled survey comparing cancer patients' preferences of AI- to physician-generated empathic statements. Physicians and AI were provided the same prompt with a maximum sentence length. Patient preferences for each statement were measured in blinded surveys. We analyzed sentiment of the statements using the Valence Aware Dictionary and Sentiment Reasoner (VADER) and the National Research Council Canada (NRC) Emotion Lexicon. We evaluated associations between sentiment scores and patient preferences using Spearman's correlation coefficients. RESULTS: A total of 105 patients completed blinded surveys, preferring the AI-generated statement 72.4% of the time. VADER sentiment analysis showed all three AI statements displayed positive sentiment, while all three physician statements displayed negative sentiment. Controlling for statement length, AI statements used twice as many positive words as human statements. However, they contained a similar number of negative words. Of the eight NRC emotions, "trust" and "joy" demonstrated the strongest correlations with patient preference. CONCLUSION: Patients preferred AI-generated statements around cancer care over those from palliative care physicians when standardized for prompt and statement length. Analysis shows AI-generated statements contain more positive language which may be the factor driving patient preference toward AI.

Humans↗
PubMed2005

Deformational brachycephaly in supine-sleeping infants.

OBJECTIVES: Medical dictionaries and anthropologic sources define brachycephaly as a cranial index (CI = width divided by length x 100%) greater than 81%. We examine the impact of supine sleeping on CI and compare orthotic treatment with repositioning. STUDY DESIGN: We compared the effect of repositioning versus helmet therapy on CI in 193 infants referred for abnormal head shape. RESULTS: Eighty percent of the infants had a pretreatment CI > 81%. Their initial mean CI at mean age 5.3 months was 89%, and after treatment, their mean CI was 87% (+/-2 SE = 0.9%) at mean age 9.0 months. For 92 infants with an initial CI at or above 90%, their initial mean CI of 96.1% was reduced to a mean of 91.9%. CONCLUSIONS: Post-treatment CI was 86% to 88%, CI in neonates delivered by cesarean section was 80%, and CI in supine-sleeping Asian children was 85% to 91%, versus 78% to 83% for prone-sleeping American children. Repositioning was less effective than cranial orthotic therapy in correcting severe brachycephaly. We recommend varying the head position when putting infants to sleep.

Female↗
PubMed2005

Feature detection using spikes: the greedy approach.

A goal of low-level neural processes is to build an efficient code extracting the relevant information from the sensory input. It is believed that this is implemented in cortical areas by elementary inferential computations dynamically extracting the most likely parameters corresponding to the sensory signal. We explore here a neuro-mimetic feed-forward model of the primary visual area (VI) solving this problem in the case where the signal may be described by a robust linear generative model. This model uses an over-complete dictionary of primitives which provides a distributed probabilistic representation of input features. Relying on an efficiency criterion, we derive an algorithm as an approximate solution which uses incremental greedy inference processes. This algorithm is similar to 'Matching Pursuit' and mimics the parallel architecture of neural computations. We propose here a simple implementation using a network of spiking integrate-and-fire neurons which communicate using lateral interactions. Numerical simulations show that this Sparse Spike Coding strategy provides an efficient model for representing visual data from a set of natural images. Even though it is simplistic, this transformation of spatial data into a spatio-temporal pattern of binary events provides an accurate description of some complex neural patterns observed in the spiking activity of biological neural networks.

Action Potentials↗
PubMed2007

The diagnostic workup of patients with neuropathic pain.

Determining the causes of neuropathic pain is more than an epistemological exercise. At its essence, it is a quest to delineate mechanisms of dysfunction through which treatment strategies can be created that are effective in reducing, ameliorating, or eliminating symptomatology. To date, predictors of which patients will develop neuropathic pain or who will respond to specific therapies are lacking, and present therapies have been developed mainly through trial and error. Our current inability to make therapeutically meaningful decisions based on ancillary test data is illustrated by the following: In a study specifically designed to assess the response of patients with painful distal sensory neuropathies to the 5% lidocaine patch, no relationship between treatment response and distal leg skin biopsy, QST, or sensory nerve conduction study results could be established. From a mechanistic perspective, the hypothesis that the lidocaine patch would be most effective in patients with relatively intact epidermal innervation, whose neuropathic pain is presumed attributable to "irritable nociceptors," and least effective in patients with few surviving epidermal nociceptors, presumably with "deafferentation pain," was unproven. The possible explanations are multiple and outside the scope of this review. However, these findings, coupled with the disparity in C-fiber subtype involvement in diabetic small-fiber neuropathy, and the recently reported inability of enzyme replacement therapy in Fabry disease to influence intraepidermal innervation density, while having mixed effects on cold and warm QST thresholds, and beneficial effects on sudomotor findings, when therapeutic benefit was demonstrated, lead one to conclude that the specificity of ancillary testing in neuropathic pain is inadequate at present, and reinforce the aforementioned caveats about inferential conclusions from indirect data. The diagnosis of neuropathic pain mechanisms is in its nascent stages and ancillary testing remains "subordinate," "subsidiary," and "auxiliary" as defined in Webster's Third New International Dictionary. As a consequence of these difficulties, the recent approach by Bennett and his colleagues may have merit. They have hypothesized (and provide data in support) that chronic pain can be more or less neuropathic on a spectrum between "likely," "possible," and "unlikely," based on patient responses on validated neuropathic pain symptom scales, when compared with specialist pain physician certainty of the presence of neuropathic pain on a 100-mm visual analog scale. The symptoms most associated with neuropathic pain were dysesthesias, evoked pain, paroxysmal pain, thermal pain, autonomic complaints, and descriptions of the pain as being sharp, hot, or cold, with high sensitivity. Higher scores for these symptoms correlated with greater clinician certainty of the presence of neuropathic pain mechanisms. Considering each individual patient's chronic pain as being somewhere on a continuum between "purely nociceptive" and "purely neuropathic" may have diagnostic and therapeutic relevance by enhancing specificity, but this requires clinical confirmation. Thus, symptom assessment remains indispensable in the evaluation of neuropathic pain, ancillary testing notwithstanding

Autonomic Nervous System↗
PubMed2006

Noise reduction in Doppler ultrasound signals using an adaptive decomposition algorithm.

A novel de-noising method for improving the signal-to-noise ratio (SNR) of Doppler ultrasound blood flow signals, called the matching pursuit method, has been proposed. Using this method, the Doppler ultrasound signal was first decomposed into a linear expansion of waveforms, called time-frequency atoms, which were selected from a redundant dictionary named Gabor functions. Subsequently, a decay parameter-based algorithm was employed to determine the decomposition times. Finally, the de-noised Doppler signal was reconstructed using the selected components. The SNR improvements, the amount of the lost component in the original signal and the maximum frequency estimation precision with simulated Doppler blood flow signals, have been used to evaluate a performance comparison, based on the wavelet, the wavelet packets and the matching pursuit de-noising algorithms. From the simulation and clinical experiment results, it was concluded that the performance of the matching pursuit approach was better than those of the DWT and the WPs methods for the Doppler ultrasound signal de-noising.

Algorithms↗
PubMedDate not supplied

Online algorithm for the self-organizing map of symbol strings.

In this work an online algorithm is presented for the construction of the self-organizing map (SOM) of symbol strings. Each node of the SOM grid is associated with a model string which is a variable-vector sequence. Smooth interpolation method is applied in the training which performs simultaneous adaptation of the symbol content and the length of the model string. The efficiency of the method is demonstrated by the clustering of a 100,000-word English dictionary.

Algorithms↗
PubMed2004

Bootstrapped DEPICT for error estimation in PET functional imaging.

Basis pursuit denoising is a new approach for data-driven estimation of parametric images from dynamic positron emission tomography (PET) data. At present, this kinetic modeling technique does not allow for the estimation of the errors on the parameters. These estimates are useful when performing subsequent statistical analysis, such as, inference across a group of subjects or when applying partial volume correction algorithms. The difficulty with calculating the error estimates is a consequence of using an overcomplete dictionary of kinetic basis functions. In this paper, a bootstrap approach for the estimation of parameter errors from dynamic PET data is presented. This paper shows that the bootstrap can be used successfully to compute parameter errors on a region of interest or parametric image basis. Validation studies evaluate the methods performance on simulated and measured PET data ([(11)C]Diprenorphine-opiate receptor and [(11)C]Raclopride-dopamine D(2) receptor). The method is presented in the context of PET neuroreceptor binding studies, however, it has general applicability to a wide range of PET/SPET radiotracers in neurology, oncology and cardiology.

Adult↗
PubMed2005

Representation of ophthalmology concepts by electronic systems: adequacy of controlled medical terminologies.

OBJECTIVE: To assess the adequacy of 5 controlled medical terminologies (International Classification of Diseases 9, Clinical Modification [ICD9-CM]; Current Procedural Terminology 4 [CPT-4]; Systematized Nomenclature of Medicine, Clinical Terms [SNOMED-CT]; Logical Identifiers, Names, and Codes [LOINC]; Medical Entities Dictionary [MED]) for representing concepts in ophthalmology. DESIGN: Noncomparative case series. PARTICIPANTS: Twenty complete ophthalmology case presentations were sequentially selected from a publicly available ophthalmology journal. METHODS: Each of the 20 cases was parsed into discrete concepts, and each concept was classified along 2 axes: (1) diagnosis, finding, or procedure and (2) ophthalmic or medical concept. Electronic or paper browsers were used to assign a code for every concept in each of the 5 terminologies. Adequacy of assignment for each concept was scored on a 3-point scale. Findings from all 20 case presentations were combined and compared based on a coverage score, which was the average score for all concepts in that terminology. MAIN OUTCOME MEASURES: Adequacy of assignment for concepts in each terminology, based on a 3-point Likert scale (0, no match; 1, partial match; 2, complete match). RESULTS: Cases were parsed into 1603 concepts. SNOMED-CT had the highest mean overall coverage score (1.625+/-0.667), followed by MED (0.974+/-0.764), LOINC (0.781+/-0.929), ICD9-CM (0.280+/-0.619), and CPT-4 (0.082+/-0.337). SNOMED-CT also had higher coverage scores than any of the other terminologies for concepts in the diagnosis, finding, and procedure categories. Average coverage scores for ophthalmic concepts were lower than those for medical concepts. CONCLUSIONS: Controlled terminologies are required for electronic representation of ophthalmology data. SNOMED-CT had significantly higher content coverage than any other terminology in this study.

Humans↗
PubMed2006

Representation of ophthalmology concepts by electronic systems: intercoder agreement among physicians using controlled terminologies.

OBJECTIVE: To assess intercoder agreement for ophthalmology concepts by 3 physician coders using 5 controlled terminologies (International Classification of Diseases 9, Clinical Modification [ICD9CM]; Current Procedural Terminology, fourth edition; Logical Observation Identifiers, Names, and Codes [LOINC]; Systematized Nomenclature of Medicine, Clinical Terms [SNOMED-CT]; and Medical Entities Dictionary). DESIGN: Noncomparative case series. PARTICIPANTS: Five complete ophthalmology case presentations selected from a publicly available journal. METHODS: Each case was parsed into discrete concepts. Electronic or paper browsers were used independently by 3 physician coders to assign a code for every concept in each terminology. A match score representing adequacy of assignment for each concept was assigned on a 3-point scale (0, no match; 1, partial match; 2, complete match). For every concept, the level of intercoder agreement was determined by 2 methods: (1) based on exact code matching with assignment of complete agreement when all coders assigned the same code, partial agreement when 2 coders assigned the same code, and no agreement when all coders assigned different codes, and (2) based on manual review for semantic equivalence of all assigned codes by an independent ophthalmologist to classify intercoder agreement for each concept as complete agreement, partial agreement, or no agreement. Subsequently, intercoder agreement was calculated in the same manner for the subset of concepts judged to have adequate coverage by each terminology, based on receiving a match score of 2 by at least 2 of the 3 coders. MAIN OUTCOME MEASURES: Intercoder agreement in each controlled terminology: complete, partial, or none. RESULTS: Cases were parsed into 242 unique concepts. When all concepts were analyzed by manual review, the proportion of complete intercoder agreement ranged from 12% (LOINC) to 44% (SNOMED-CT), and the difference in intercoder agreement between LOINC and all other terminologies was statistically significant (P<0.004). When only concepts with adequate terminology were analyzed by manual review, the proportion of complete intercoder agreement ranged from 33% (LOINC) to 64% (ICD9CM), and there were no statistically significant differences in intercoder agreement among any pairs of terminologies. CONCLUSIONS: The level of intercoder agreement for ophthalmic concepts in existing controlled medical terminologies is imperfect. Intercoder reproducibility is essential for accurate and consistent electronic representation of medical data.

Decision Support Systems, Clinical↗
PubMed2004

An alternative view of the mental lexicon.

An essential aspect of knowing language is knowing the words of that language. This knowledge is usually thought to reside in the mental lexicon, a kind of dictionary that contains information regarding a word's meaning, pronunciation, syntactic characteristics, and so on. In this article, a very different view is presented. In this view, words are understood as stimuli that operate directly on mental states. The phonological, syntactic and semantic properties of a word are revealed by the effects it has on those states.

Humans↗