927 resultados para Computer based training
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Background Patients often establish initial contact with healthcare institutions by telephone. During this process they are frequently medically triaged. Purpose To investigate the safety of computer-assisted telephone triage for walk-in patients with non-life-threatening medical conditions at an emergency unit of a Swiss university hospital. Methods This prospective surveillance study compared the urgency assessments of three different types of personnel (call centre nurses, hospital physicians, primary care physicians) who were involved in the patients' care process. Based on the urgency recommendations of the hospital and primary care physicians, cases which could potentially have resulted in an avoidable hazardous situation (AHS) were identified. Subsequently, the records of patients with a potential AHS were assessed for risk to health or life by an expert panel. Results 208 patients were enrolled in the study, of whom 153 were assessed by all three types of personnel. Congruence between the three assessments was low. The weighted κ values were 0.115 (95% CI 0.038 to 0.192) (hospital physicians vs call centre), 0.159 (95% CI 0.073 to 0.242) (primary care physicians vs call centre) and 0.377 (95% CI 0.279 to 0.480) (hospital vs primary care physicians). Seven of 153 cases (4.57%; 95% CI 1.85% to 9.20%) were classified as a potentially AHS. A risk to health or life was adjudged in one case (0.65%; 95% CI 0.02% to 3.58%). Conclusion Medical telephone counselling is a demanding task requiring competent specialists with dedicated training in communication supported by suitable computer technology. Provided these conditions are in place, computer-assisted telephone triage can be considered to be a safe method of assessing the potential clinical risks of patients' medical conditions.
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Statistical models have been recently introduced in computational orthopaedics to investigate the bone mechanical properties across several populations. A fundamental aspect for the construction of statistical models concerns the establishment of accurate anatomical correspondences among the objects of the training dataset. Various methods have been proposed to solve this problem such as mesh morphing or image registration algorithms. The objective of this study is to compare a mesh-based and an image-based statistical appearance model approaches for the creation of nite element(FE) meshes. A computer tomography (CT) dataset of 157 human left femurs was used for the comparison. For each approach, 30 finite element meshes were generated with the models. The quality of the obtained FE meshes was evaluated in terms of volume, size and shape of the elements. Results showed that the quality of the meshes obtained with the image-based approach was higher than the quality of the mesh-based approach. Future studies are required to evaluate the impact of this finding on the final mechanical simulations.
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This paper presents a new approach for reconstructing a patient-specific shape model and internal relative intensity distribution of the proximal femur from a limited number (e.g., 2) of calibrated C-arm images or X-ray radiographs. Our approach uses independent shape and appearance models that are learned from a set of training data to encode the a priori information about the proximal femur. An intensity-based non-rigid 2D-3D registration algorithm is then proposed to deformably fit the learned models to the input images. The fitting is conducted iteratively by minimizing the dissimilarity between the input images and the associated digitally reconstructed radiographs of the learned models together with regularization terms encoding the strain energy of the forward deformation and the smoothness of the inverse deformation. Comprehensive experiments conducted on images of cadaveric femurs and on clinical datasets demonstrate the efficacy of the present approach.
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We present a new approach for corpus-based speech enhancement that significantly improves over a method published by Xiao and Nickel in 2010. Corpus-based enhancement systems do not merely filter an incoming noisy signal, but resynthesize its speech content via an inventory of pre-recorded clean signals. The goal of the procedure is to perceptually improve the sound of speech signals in background noise. The proposed new method modifies Xiao's method in four significant ways. Firstly, it employs a Gaussian mixture model (GMM) instead of a vector quantizer in the phoneme recognition front-end. Secondly, the state decoding of the recognition stage is supported with an uncertainty modeling technique. With the GMM and the uncertainty modeling it is possible to eliminate the need for noise dependent system training. Thirdly, the post-processing of the original method via sinusoidal modeling is replaced with a powerful cepstral smoothing operation. And lastly, due to the improvements of these modifications, it is possible to extend the operational bandwidth of the procedure from 4 kHz to 8 kHz. The performance of the proposed method was evaluated across different noise types and different signal-to-noise ratios. The new method was able to significantly outperform traditional methods, including the one by Xiao and Nickel, in terms of PESQ scores and other objective quality measures. Results of subjective CMOS tests over a smaller set of test samples support our claims.
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Many research-based instruction strategies (RBISs) have been developed; their superior efficacy with respect to student learning has been demonstrated in many studies. Collecting and interpreting evidence about: 1) the extent to which electrical and computer engineering (ECE) faculty members are using RBISs in core, required engineering science courses, and 2) concerns that they express about using them, are important aspects of understanding how engineering education is evolving. The authors surveyed ECE faculty members, asking about their awareness and use of selected RBISs. The survey also asked what concerns ECE faculty members had about using RBISs. Respondent data showed that awareness of RBISs was very high, but estimates of use of RBISs, based on survey data, varied from 10% to 70%, depending on characteristics of the strategy. The most significant concern was the amount of class time that using an RBIS might take; efforts to increase use of RBISs must address this.
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A set of algorithms, which allows a computer to determine the answers of simulated patients during pure tone and speech audiometry, is presented. Based on these algorithms, a computer program for training in audiometry was written and found to be useful for teaching purposes.
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OBJECTIVE: To design and evaluate a novel computer-assisted, fluoroscopy-based planning and navigation system for minimally invasive ventral spondylodesis of thoracolumbar fractures. MATERIALS AND METHODS: Instruments and an image intensifier are tracked with the SurgiGATE navigation system (Praxim-Medivision). Two fluoroscopic images, one acquired from anterior-posterior (AP) direction and the other from lateral-medial (LM) direction, are used for the complete procedure of planning and navigation. Both of them are calibrated with a custom-made software to recover their projection geometry and to co-register them to a common patient reference coordinate system, which is established by attaching an opto-electronically trackable dynamic reference base (DRB) on the operated vertebra. A bi-planar landmark reconstruction method is used to acquire deep-seated anatomical landmarks such that an intraoperative planning of graft bed can be interactively done. Finally, surgical actions such as the placement of the stabilization devices and the formation of the graft bed using a custom-made chisel are visualized to the surgeon by superimposing virtual instrument representations onto the acquired images. The distance between the instrument tip and each wall of the planned graft bed are calculated on the fly and presented to the surgeon so that the surgeon could formalize the graft bed exactly according to his/her plan. RESULTS: Laboratory studies on phantom and on 27 plastic vertebras demonstrate the high precision of the proposed navigation system. Compared with CT-based measurement, a mean error of 1.0 mm with a standard deviation of 0.1 mm was found. CONCLUSIONS: The proposed computer assisted, fluoroscopy-based planning and navigation system promises to increase the accuracy and reliability of minimally invasive ventral spondylodesis of thoracolumbar fractures.