942 resultados para software, translation, validation tool, VMNET, Wikipedia, XML


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BACKGROUND: The aim of this study was to develop a child-specific classification system for long bone fractures and to examine its reliability and validity on the basis of a prospective multicentre study. METHODS: Using the sequentially developed classification system, three samples of between 30 and 185 paediatric limb fractures from a pool of 2308 fractures documented in two multicenter studies were analysed in a blinded fashion by eight orthopaedic surgeons, on a total of 5 occasions. Intra- and interobserver reliability and accuracy were calculated. RESULTS: The reliability improved with successive simplification of the classification. The final version resulted in an overall interobserver agreement of κ = 0.71 with no significant difference between experienced and less experienced raters. CONCLUSIONS: In conclusion, the evaluation of the newly proposed classification system resulted in a reliable and routinely applicable system, for which training in its proper use may further improve the reliability. It can be recommended as a useful tool for clinical practice and offers the option for developing treatment recommendations and outcome predictions in the future.

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Purpose Physiological respiratory motion of tumors growing in the lung can be corrected with respiratory gating when treated with radiotherapy (RT). The optimal respiratory phase for beam-on may be assessed with a respiratory phase optimizer (RPO), a 4D image processing software developed with this purpose. Methods and Materials Fourteen patients with lung cancer were included in the study. Every patient underwent a 4D-CT providing ten datasets of ten phases of the respiratory cycle (0-100% of the cycle). We defined two morphological parameters for comparison of 4D-CT images in different respiratory phases: tumor-volume to lung-volume ratio and tumor-to-spinal cord distance. The RPO automatized the calculations (200 per patient) of these parameters for each phase of the respiratory cycle allowing to determine the optimal interval for RT. Results Lower lobe lung tumors not attached to the diaphragm presented with the largest motion with breathing. Maximum inspiration was considered the optimal phase for treatment in 4 patients (28.6%). In 7 patients (50%), however, the RPO showed a most favorable volumetric and spatial configuration in phases other than maximum inspiration. In 2 cases (14.4%) the RPO showed no benefit from gating. This tool was not conclusive in only one case. Conclusions The RPO software presented in this study can help to determine the optimal respiratory phase for gated RT based on a few simple morphological parameters. Easy to apply in daily routine, it may be a useful tool for selecting patients who might benefit from breathing adapted RT.

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With the publication of the quality guideline ICH Q9 "Quality Risk Management" by the International Conference on Harmonization, risk management has already become a standard requirement during the life cycle of a pharmaceutical product. Failure mode and effect analysis (FMEA) is a powerful risk analysis tool that has been used for decades in mechanical and electrical industries. However, the adaptation of the FMEA methodology to biopharmaceutical processes brings about some difficulties. The proposal presented here is intended to serve as a brief but nevertheless comprehensive and detailed guideline on how to conduct a biopharmaceutical process FMEA. It includes a detailed 1-to-10-scale FMEA rating table for occurrence, severity, and detectability of failures that has been especially designed for typical biopharmaceutical processes. The application for such a biopharmaceutical process FMEA is widespread. It can be useful whenever a biopharmaceutical manufacturing process is developed or scaled-up, or when it is transferred to a different manufacturing site. It may also be conducted during substantial optimization of an existing process or the development of a second-generation process. According to their resulting risk ratings, process parameters can be ranked for importance and important variables for process development, characterization, or validation can be identified. LAY ABSTRACT: Health authorities around the world ask pharmaceutical companies to manage risk during development and manufacturing of pharmaceuticals. The so-called failure mode and effect analysis (FMEA) is an established risk analysis tool that has been used for decades in mechanical and electrical industries. However, the adaptation of the FMEA methodology to pharmaceutical processes that use modern biotechnology (biopharmaceutical processes) brings about some difficulties, because those biopharmaceutical processes differ from processes in mechanical and electrical industries. The proposal presented here explains how a biopharmaceutical process FMEA can be conducted. It includes a detailed 1-to-10-scale FMEA rating table for occurrence, severity, and detectability of failures that has been especially designed for typical biopharmaceutical processes. With the help of this guideline, different details of the manufacturing process can be ranked according to their potential risks, and this can help pharmaceutical companies to identify aspects with high potential risks and to react accordingly to improve the safety of medicines.

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This paper examines the accuracy of software-based on-line energy estimation techniques. It evaluates today’s most widespread energy estimation model in order to investigate whether the current methodology of pure software-based energy estimation running on a sensor node itself can indeed reliably and accurately determine its energy consumption - independent of the particular node instance, the traffic load the node is exposed to, or the MAC protocol the node is running. The paper enhances today’s widely used energy estimation model by integrating radio transceiver switches into the model, and proposes a methodology to find the optimal estimation model parameters. It proves by statistical validation with experimental data that the proposed model enhancement and parameter calibration methodology significantly increases the estimation accuracy.

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The NIMH's new strategic plan, with its emphasis on the "4P's" (Prediction, Pre-emption, Personalization, and Populations) and biomarker-based medicine requires a radical shift in animal modeling methodology. In particular 4P's models will be non-determinant (i.e. disease severity will depend on secondary environmental and genetic factors); and validated by reverse-translation of animal homologues to human biomarkers. A powerful consequence of the biomarker approach is that different closely related disorders have a unique fingerprint of biomarkers. Animals can be validated as a highly specific model of a single disorder by matching this 'fingerprint'; or as a model of a symptom seen in multiple disorders by matching common biomarkers. Here we illustrate this approach with two Abnormal Repetitive Behaviors (ARBs) in mice: stereotypies and barbering (hair pulling). We developed animal versions of the neuropsychological biomarkers that distinguish human ARBs, and tested the fingerprint of the different mouse ARBs. As predicted, the two mouse ARBs were associated with different biomarkers. Both barbering and stereotypy could be discounted as models of OCD (even though they are widely used as such), due to the absence of limbic biomarkers which are characteristic of OCD and hence are necessary for a valid model. Conversely barbering matched the fingerprint of trichotillomania (i.e. selective deficits in set-shifting), suggesting it may be a highly specific model of this disorder. In contrast stereotypies were correlated only with a biomarker (deficits in response shifting) correlated with stereotypies in multiple disorders, suggesting that animal stereotypies model stereotypies in multiple disorders.

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PURPOSE : For the facilitation of minimally invasive robotically performed direct cochlea access (DCA) procedure, a surgical planning tool which enables the surgeon to define landmarks for patient-to-image registration, identify the necessary anatomical structures and define a safe DCA trajectory using patient image data (typically computed tomography (CT) or cone beam CT) is required. To this end, a dedicated end-to-end software planning system for the planning of DCA procedures that addresses current deficiencies has been developed. METHODS :    Efficient and robust anatomical segmentation is achieved through the implementation of semiautomatic algorithms; high-accuracy patient-to-image registration is achieved via an automated model-based fiducial detection algorithm and functionality for the interactive definition of a safe drilling trajectory based on case-specific drill positioning uncertainty calculations was developed. RESULTS :    The accuracy and safety of the presented software tool were validated during the conduction of eight DCA procedures performed on cadaver heads. The plan for each ear was completed in less than 20 min, and no damage to vital structures occurred during the procedures. The integrated fiducial detection functionality enabled final positioning accuracies of [Formula: see text] mm. CONCLUSIONS :    Results of this study demonstrated that the proposed software system could aid in the safe planning of a DCA tunnel within an acceptable time.

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OBJECTIVES: To validate the Probability of Repeated Admission (Pra) questionnaire, a widely used self-administered tool for predicting future healthcare use in older persons, in three European healthcare systems. DESIGN: Prospective study with 1-year follow-up. SETTING: Hamburg, Germany; London, United Kingdom; Canton of Solothurn, Switzerland. PARTICIPANTS: Nine thousand seven hundred thirteen independently living community-dwelling people aged 65 and older. MEASUREMENTS: Self-administered eight-item Pra questionnaire at baseline. Self-reported number of hospital admissions and physician visits during 1 year of follow-up. RESULTS: In the combined sample, areas under the receiver operating characteristic curves (AUCs) were 0.64 (95% confidence interval (CI)=0.62-0.66) for the prediction of one or more hospital admissions and 0.68 (95% CI=0.66-0.69) for the prediction of more than six physician visits during the following year. AUCs were similar between sites. In comparison, prediction models based on a person's age and sex alone exhibited poor predictive validity (AUC or= 0.5) were 2.3 times as likely (95% CI=2.1-2.6) as low-risk individuals to have a hospital admission, and 2.1 times as likely (95% CI=2.0-2.2) to have more than six physician visits. CONCLUSION: The Pra instrument exhibits good validity for predicting future health service use on a population level in different healthcare settings. Administrative data have shown similar predictive validity, but in practice, such data are often not available. The Pra is likely of high interest to governments and health insurance companies worldwide as a basis for programs aimed at health risk management in older persons.

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The use of dental processing software for computed tomography (CT) data (Dentascan) is described on postmortem (pm) CT data for the purpose of pm identification. The software allows reconstructing reformatted images comparable to conventional panoramic dental radiographs by defining a curved reconstruction line along the teeth on oblique images. Three corpses that have been scanned within the virtopsy project were used to test the software for the purpose of dental identification. In every case, dental panoramic images could be reconstructed and compared to antemortem radiographs. The images showed the basic component of teeth (enamel, dentin, and pulp), the anatomic structure of the alveolar bone, missing or unerupted teeth as well as restorations of the teeth that could be used for identification. When streak artifacts due to metal-containing dental work reduced image quality, it was still necessary to perform pm conventional radiographs for comparison of the detailed shape of the restoration. Dental identification or a dental profiling seems to become possible in a noninvasive manner using the Dentascan software.

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Data visualization is the process of representing data as pictures to support reasoning about the underlying data. For the interpretation to be as easy as possible, we need to be as close as possible to the original data. As most visualization tools have an internal meta-model, which is different from the one for the presented data, they usually need to duplicate the original data to conform to their meta-model. This leads to an increase in the resources needed, increase which is not always justified. In this work we argue for the need of having an engine that is as close as possible to the data and we present our solution of moving the visualization tool to the data, instead of moving the data to the visualization tool. Our solution also emphasizes the necessity of reusing basic blocks to express complex visualizations and allowing the programmer to script the visualization using his preferred tools, rather than a third party format. As a validation of the expressiveness of our framework, we show how we express several already published visualizations and describe the pros and cons of the approach.

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The objectives of this study were to develop and validate a tool for assessing pain in population-based observational studies and to develop three subscales for back/neck, upper extremity and lower extremity pain. Based on a literature review, items were extracted from validated questionnaires and reviewed by an expert panel. The initial questionnaire consisted of a pain manikin and 34 items relating to (i) intensity of pain in different body regions (7 items), (ii) pain during activities of daily living (18 items) and (iii) various pain modalities (9 items). Psychometric validation of the initial questionnaire was performed in a random sample of the German-speaking Swiss population. Analyses included tests for reliability, correlation analysis, principal components factor analysis, tests for internal consistency and validity. Overall, 16,634 of 23,763 eligible individuals participated (70%). Test-retest reliability coefficients ranged from 0.32 to 0.97, but only three coefficients were below 0.60. Subscales were constructed combining four items for each of the subscales. Item-total coefficients ranged from 0.76 to 0.86 and Cronbach's alpha were 0.75 or higher for all subscales. Correlation coefficients between subscales and three validated instruments (WOMAC, SPADI and Oswestry) ranged from 0.62 to 0.79. The final Pain Standard Evaluation Questionnaire (SEQ Pain) included 28 items and the pain manikin and accounted for the multidimensionality of pain by assessing pain location and intensity, pain during activity, triggers and time of onset of pain and frequency of pain medication. It was found to be reliable and valid for the assessment of pain in population-based observational studies.

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There is a need by engine manufactures for computationally efficient and accurate predictive combustion modeling tools for integration in engine simulation software for the assessment of combustion system hardware designs and early development of engine calibrations. This thesis discusses the process for the development and validation of a combustion modeling tool for Gasoline Direct Injected Spark Ignited Engine with variable valve timing, lift and duration valvetrain hardware from experimental data. Data was correlated and regressed from accepted methods for calculating the turbulent flow and flame propagation characteristics for an internal combustion engine. A non-linear regression modeling method was utilized to develop a combustion model to determine the fuel mass burn rate at multiple points during the combustion process. The computational fluid dynamic software Converge ©, was used to simulate and correlate the 3-D combustion system, port and piston geometry to the turbulent flow development within the cylinder to properly predict the experimental data turbulent flow parameters through the intake, compression and expansion processes. The engine simulation software GT-Power © is then used to determine the 1-D flow characteristics of the engine hardware being tested to correlate the regressed combustion modeling tool to experimental data to determine accuracy. The results of the combustion modeling tool show accurate trends capturing the combustion sensitivities to turbulent flow, thermodynamic and internal residual effects with changes in intake and exhaust valve timing, lift and duration.

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In the realm of computer programming, the experience of writing a program is used to reinforce concepts and evaluate ability. This research uses three case studies to evaluate the introduction of testing through Kolb's Experiential Learning Model (ELM). We then analyze the impact of those testing experiences to determine methods for improving future courses. The first testing experience that students encounter are unit test reports in their early courses. This course demonstrates that automating and improving feedback can provide more ELM iterations. The JUnit Generation (JUG) tool also provided a positive experience for the instructor by reducing the overall workload. Later, undergraduate and graduate students have the opportunity to work together in a multi-role Human-Computer Interaction (HCI) course. The interactions use usability analysis techniques with graduate students as usability experts and undergraduate students as design engineers. Students get experience testing the user experience of their product prototypes using methods varying from heuristic analysis to user testing. From this course, we learned the importance of the instructors role in the ELM. As more roles were added to the HCI course, a desire arose to provide more complete, quality assured software. This inspired the addition of unit testing experiences to the course. However, we learned that significant preparations must be made to apply the ELM when students are resistant. The research presented through these courses was driven by the recognition of a need for testing in a Computer Science curriculum. Our understanding of the ELM suggests the need for student experience when being introduced to testing concepts. We learned that experiential learning, when appropriately implemented, can provide benefits to the Computer Science classroom. When examined together, these course-based research projects provided insight into building strong testing practices into a curriculum.

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Our goal was to validate accuracy, consistency, and reproducibility/reliability of a new method for determining cup orientation in total hip arthroplasty (THA). This method allows matching the 3D-model from CT images or slices with the projected pelvis on an anteroposterior pelvic radiograph using a fully automated registration procedure. Cup orientation (inclination and anteversion) is calculated relative to the anterior pelvic plane, corrected for individual malposition of the pelvis during radiograph acquisition. Measurements on blinded and randomized radiographs of 80 cadaver and 327 patient hips were investigated. The method showed a mean accuracy of 0.7 +/- 1.7 degrees (-3.7 degrees to 4.0 degrees) for inclination and 1.2 +/- 2.4 degrees (-5.3 degrees to 5.6 degrees) for anteversion in the cadaver trials and 1.7 +/- 1.7 degrees (-4.6 degrees to 5.5 degrees) for inclination and 0.9 +/- 2.8 degrees (-5.2 degrees to 5.7 degrees) for anteversion in the clinical data when compared to CT-based measurements. No systematic errors in accuracy were detected with the Bland-Altman analysis. The software consistency and the reproducibility/reliability were very good. This software is an accurate, consistent, reliable, and reproducible method to measure cup orientation in THA using a sophisticated 2D/3D-matching technique. Its robust and accurate matching algorithm can be expanded to statistical models.

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OBJECTIVE: The aim of this study was to establish and validate a three-dimensional imaging protocol for the assessment of Computed Tomography (CT) scans of abdominal aortic aneurysms in UK EVAR trials patients. Quality control and repeatability of anatomical measurements is important for the validity of any core laboratory. METHODS: Three different observers performed anatomical measurements on 50 preoperative CT scans of aortic aneurysms using the Vitrea 2 three-dimensional post-imaging software in a core laboratory setting. We assessed the accuracy of intra and inter observer repeatability of measurements, the time required for collection of measurements, 3 different levels of automation and 3 different automated criteria for measurement of neck length. RESULTS: None of the automated neck length measurements demonstrated sufficient accuracy and it was necessary to perform checking of the important automated landmarks. Good intra and limited inter observer agreement were achieved with three-dimensional assessment. Complete assessment of the aneurysm and iliacs took an average (SD) of 17.2 (4.1) minutes. CONCLUSIONS: Aortic aneurysm anatomy can be assessed reliably and quickly using three-dimensional assessment but for scans of limited quality, manual checking of important landmarks remains necessary. Using a set protocol, agreement between observers is satisfactory but not as good as within observers.