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At least 973 records · Page 54Linked to original sources
PubMed2000

Airway pressure with chest compressions versus Heimlich manoeuvre in recently dead adults with complete airway obstruction.

In a previous case report a standard chest compression successfully removed a foreign body from the airway after the Heimlich manoeuvre had failed. Based on this case, standard chest compressions and Heimlich manoeuvres were performed by emergency physicians on 12 unselected cadavers with a simulated complete airway obstruction in a randomised crossover design. The mean peak airway pressure was significantly lower with abdominal thrusts compared to chest compressions, 26.4+/-19.8 cmH(2)O versus 40.8+/-16.4 cmH(2)O, respectively (P=0.005, 95% confidence interval for the mean difference 5.3-23.4 cmH(2)O). Standard chest compressions therefore have the potential of being more effective than the Heimlich manoeuvre for the management of complete airway obstruction by a foreign body in an unconscious patient. Removal of the Heimlich manoeuvre from the resuscitation algorithm for unconscious patients with suspected airway obstruction will also simplify training.

Adult↗
PubMed1997

Effect of lossy data compression on quantitative coronary measurements.

With the accepted use of (lossy) data compression at low compression factors (2, 3 and 4 on the Philips DCI), the question was posed whether higher lossy compression ratios can also be used without statistically affecting the results of quantitative coronary arteriography. In this study the influence of two data compression schemes (LOT and JPEG) at three different compression factors (5, 8 and 12) on coronary measurements was assessed with the Automated Coronary Analysis (ACA) package. A series of 30 original acquired digital images were compressed and decompressed at the different factors, and together with the original non-compressed images processed using the ACA package. In these images a total of 37 obstructed coronary segments were analyzed twice to assess the intra-observer variabilities in the obstruction and reference diameters and in the percent diameter stenosis. The results of the first and second measurements in each image were averaged, and from the differences in corresponding images with different compression ratios, the inter-compression variability was obtained. The results show that the intra-observer systematic errors in the absolute diameters are all small (< 0.07 mm), and statistically not significantly different. The intra-observer random errors for the compressed/decompressed series, however, were all larger (up to 0.21 mm) than for the original series (< 0.13 mm). Statistically significant differences in the intra-observer random errors were found for the JPEG compression scheme at a compression ratio of 5 and for the LOT scheme at a compression ratio of 12. The inter-compression systematic errors in the absolute diameter measurements were also small (< 0.07 mm) and not significant, while the random errors were found to be high in the range between 0.23 mm and 0.31 mm. Given the higher intra-observer variabilities for the compressed/decompressed image series as compared to original images, and the fact that all inter-compression variabilities were found to be so high, we must conclude that the higher compression ratios affect the results of QCA in a negative sense. In conclusion, the use of lossy data compression with JPEG or LOT compression schemes at ratios 5, 8 and 12 must be discouraged for QCA.

Algorithms↗
PubMed2005

Anisotropic multi-scale fluid registration: evaluation in magnetic resonance breast imaging.

Registration using models of compressible viscous fluids has not found the general application of some other techniques (e.g., free-form-deformation (FFD)) despite its ability to model large diffeomorphic deformations. We report on a multi-resolution fluid registration algorithm which improves on previous work by (a) directly solving the Navier-Stokes equation at the resolution of the images, (b) accommodating image sampling anisotropy using semi-coarsening and implicit smoothing in a full multi-grid (FMG) solver and (c) exploiting the inherent multi-resolution nature of FMG to implement a multi-scale approach. Evaluation is on five magnetic resonance (MR) breast images subject to six biomechanical deformation fields over 11 multi-resolution schemes. Quantitative assessment is by tissue overlaps and target registration errors and by registering using the known correspondences rather than image features to validate the fluid model. Context is given by comparison with a validated FFD algorithm and by application to images of volunteers subjected to large applied deformation. The results show that fluid registration of 3D breast MR images to sub-voxel accuracy is possible in minutes on a 1.6 GHz Linux-based Athlon processor with coarse solutions obtainable in a few tens of seconds. Accuracy and computation time are comparable to FFD techniques validated for this application.

Algorithms↗
PubMed1994

Back-propagation and counter-propagation neural networks for phylogenetic classification of ribosomal RNA sequences.

A neural network system has been developed for rapid and accurate classification of ribosomal RNA sequences according to phylogenetic relationship. The molecular sequences are encoded into neural input vectors using an n-gram hashing method. A SVD (singular value decomposition) method is used to compress and reduce the size of long and sparse n-gram input vectors. The neural networks used are three-layered, feed-forward networks that employ supervised learning paradigms, including the back-propagation algorithm and a modified counter-propagation algorithm. A pedagogical pattern selection strategy is used to reduce the training time. After trained with ribosomal RNA sequences of the RDP (Ribosomal Database Project) database, the system can classify query sequences into more than one hundred phylogenetic classes with a 100% accuracy at a rate of less than 0.3 CPU second per sequence on a workstation. When compared to other sequence similarity search methods, including Similarity Rank, Blast and Fasta, the neural network method has a higher classification accuracy at a speed of about an order of magnitude faster. The software tool will be made available to the biology community, and the system may be extended into a gene identification system for classifying indiscriminately sequenced DNA fragments.

Algorithms↗
PubMed1999

Design and implementation of a novel compression method in a tele-ultrasound system.

This paper represents a novel compression method for ultrasound images in a tele-ultrasound system. The encoder chooses the ultrasound scan line signals as the object to be compressed and transmitted other than the standard video images in conventional methods. Furthermore, nonuniform discrete wavelet transform is proposed considering the different resolutions in axial and lateral directions of ultrasound images. Experimental results show that the new method provides better compression performance than conventional methods in terms of a peak signal-to-noise ratio and processing time.

Algorithms↗
PubMed2001

CT data storage reduction by means of compressing projection data instead of images: feasibility study.

The authors developed and evaluated a technique of compressing raw projection data at computed tomography (CT). Raw projection data acquired at CT were compressed and decompressed and then used for image reconstruction. For comparison, original images were compressed by comparable ratios. Projection data files were more compressible than image files. Projection data compression is a promising, efficient method to reduce data file size and thus to facilitate retrospective image reconstruction.

Algorithms↗
PubMed2002

Many-layered learning.

We explore incremental assimilation of new knowledge by sequential learning. Of particular interest is how a network of many knowledge layers can be constructed in an on-line manner, such that the learned units represent building blocks of knowledge that serve to compress the overall representation and facilitate transfer. We motivate the need for many layers of knowledge, and we advocate sequential learning as an avenue for promoting the construction of layered knowledge structures. Finally, our novel STL algorithm demonstrates a method for simultaneously acquiring and organizing a collection of concepts and functions as a network from a stream of unstructured information.

Algorithms↗
PubMed2001

The physiological kinetics of nitrogen and the prevention of decompression sickness.

Decompression sickness (DCS) is a potentially crippling disease caused by intracorporeal bubble formation during or after decompression from a compressed gas underwater dive. Bubbles most commonly evolve from dissolved inert gas accumulated during the exposure to increased ambient pressure. Most diving is performed breathing air, and the inert gas of interest is nitrogen. Divers use algorithms based on nitrogen kinetic models to plan the duration and degree of exposure to increased ambient pressure and to control their ascent rate. However, even correct execution of dives planned using such algorithms often results in bubble formation and may result in DCS. This reflects the importance of idiosyncratic host factors that are difficult to model, and deficiencies in current nitrogen kinetic models. Models describing the exchange of nitrogen between tissues and blood may be based on distributed capillary units or lumped compartments, either of which may be perfusion- or diffusion-limited. However, such simplistic models are usually poor predictors of experimental nitrogen kinetics at the organ or tissue level, probably because they fail to account for factors such as heterogeneity in both tissue composition and blood perfusion and non-capillary exchange mechanisms. The modelling of safe decompression procedures is further complicated by incomplete understanding of the processes that determine bubble formation. Moreover, any formation of bubbles during decompression alters subsequent nitrogen kinetics. Although these factors mandate complex resolutions to account for the interaction between dissolved nitrogen kinetics and bubble formation and growth, most decompression schedules are based on relatively simple perfusion-limited lumped compartment models of blood: tissue nitrogen exchange. Not surprisingly, all models inevitably require empirical adjustment based on outcomes in the field. Improvements in the predictive power of decompression calculations are being achieved using probabilistic bubble models, but divers will always be subject to the possibility of developing DCS despite adherence to prescribed limits.

Algorithms↗
PubMed2001

[Content-based medical image retrieval].

At first, the concept of medical image retrieval based on contents is here illustrated. Then, features of medical image are analyzed. Among them, gray histogram method, texture method, shape method are discussed, and the compression method is emphasized. Finally, the challenges in medical image retrieval are presented before us in the paper.

Algorithms↗
PubMed2003

[Diagnostic strategies of thrombo-embolic venous disease].

The advent of non invasive tests (D-dimer and lower limb venous compression ultrasonography) and minimally invasive tests (helical CT scan) and the rehabilitation of clinical assessment have allowed the development of safe, rational and cost-effective diagnostic strategies for deep venous thrombosis and pulmonary embolism. Several algorithms have been validated in studies in which patients classified as not having venous thromboembolism are left untreated and followed up during 3 months. The safety of such strategies is established by comparing the 3-month thromboembolic risk in such patients with that of patients left untreated based on a normal venogram, pulmonary angiogram or lung scintigram. Venography or pulmonary angiography remains necessary in selected cases such as patients with a high clinical probability of venous thromboembolism and an inconclusive non invasive workup, representing only approximately 5 to 10% of all patients. Finally, suspected massive pulmonary embolism is a distinct clinical situation in which echocardiography plays a major role.

Algorithms↗
PubMedDate not supplied

[The role of computer methods in the diagnosis of mono- and multifactorial traumatic compression of the brain].

A scheme of differential diagnosis of mono- and multifactor compression of the brain was formed on the grounds of 18 most frequently encountered signs of the injury. The work is based on 693 cases which were verified on operation. The results were checked on a large independent selection. Accuracy of recognition was 87.5%. The Table suggested by the authors may prove valuable in emergency situations when the patients are admitted in a serious condition, in impetuous development of the compression syndrome, and when there is lack of time for carrying out instrumental examination.

Adult↗
PubMed2004

Autoregressive modeling of analytical sensor data can yield classifiers in the predictor coefficient parameter space.

SUMMARY: The analysis of chromatographic data resulting from complex chemical mixtures is challenging. Components may co-elute, causing their signals to overlap. An algorithm that will increase the signal-to-noise ratio so compounds present in low abundance can be better distinguished from noise is useful in this type of analysis. The autoregressive (AR) filter offers the advantage of smoothing chromatograms to increase this ratio, while also offering data compression and increased resolution. Furthermore, this filter can be useful for classification, as the roots of the predictor coefficient vectors represent features present in the data and can therefore be used for pattern recognition. In this paper, we present a novel method for applying AR filtering to chromatogram data. We show that the AR filter outperforms the Savitzky-Golay filter for smoothing noise while retaining important information within chromatograms, and also that AR correlation coefficients have the potential to be used to classify chromatogram data into groups. CONTACT: cdavis@draper.com.

Algorithms↗
PubMed2002

Analysis of identifier performance using a deterministic linkage algorithm.

As part of developing a record linkage algorithm using de-identified patient data, we analyzed the performance of several demographic variables for making linkages between patient registry records from two hospital registries and the Social Security Death Master File. We analyzed samples from each registry totaling 6,000 record-pairs to establish a linkage gold-standard. Using Social Security Number as the exclusive linkage variable resulted in substantial linkage error rates of 4.7% and 9.2%. The best single variable combination for finding links was Social Security Number, phonetically compressed first name, birth month, and gender. This found 87% and 88% of the links without any false links. We achieved sensitivities of 90% to 92% while maintaining 100% specificity using combinations of social security number, gender, name, and birth date fields. This represents an accurate method for linking patient records to death data and is the basis for a more generalized de-identified linkage algorithm.

Algorithms↗
PubMed2001

Cost-effective diagnosis of deep vein thrombosis and pulmonary embolism.

Suspected acute venous thromboembolism is a frequent and challenging clinical problem. Phlebography and pulmonary angiography are costly and invasive and, hence, ill-suited for diagnosing a disease present in only 20% of patients in whom it is suspected. Novel noninvasive instruments, such as plasma D-dimer measurement, lower limb compression ultrasonography and helical CT scan are important breakthroughs in the management of patients with suspected venous thromboembolism. However, none of these instruments is ideal, and they must be combined in rational and cost-effective diagnostic algorithms including clinical assessment, which is increasingly standardized. Such strategies must be validated in management studies, in which patients without venous thromboembolism are not treated and followed up during 3 months. Suspected massive pulmonary embolism is a distinct clinical situation requiring a specific diagnostic approach, in which echocardiography plays a major role. This paper reviews the performance of clinical evaluation and diagnostic tests for venous thromboembolism, and recently validated diagnostic schemes.

Algorithms↗
PubMedDate not supplied

[Mechanical deformations of bioconstructions during different stages of morphogenesis].

The stress-deformation regularities of the body behaviour are taken as principal pattern formation factors in bioconstructions: mutually compressed cap rays of Acetabularia and contiguous tissue layers (the model). With the growth of rays or layers mechanical tensions which are initiated in them increase. If no morphogenetic loss of shape stability is resulted, an alternative algorithm of natural complication of their initial pattern is finally realized and ruptures, shifts and other deformations are formed in some weakened elements of the constructions. Among rigid stable parameters of biomaterials and geometric parameters of bioconstructions only the latter prove to be the determining ones in feasibility criterion of this or that extreme case of pattern formation (with the loss of stability or fractures). Restrictions imposed to the values of possible deformations are conditioned in case of the loss of pattern stability by geometric parameter, in case of fractures--by the strength parameters.

Acetabularia↗
PubMed1998

Distributed ARTMAP: a neural network for fast distributed supervised learning.

Distributed coding at the hidden layer of a multi-layer perceptron (MLP) endows the network with memory compression and noise tolerance capabilities. However, an MLP typically requires slow off-line learning to avoid catastrophic forgetting in an open input environment. An adaptive resonance theory (ART) model is designed to guarantee stable memories even with fast on-line learning. However, ART stability typically requires winner-take-all coding, which may cause category proliferation in a noisy input environment. Distributed ARTMAP (dARTMAP) seeks to combine the computational advantages of MLP and ART systems in a real-time neural network for supervised learning. An implementation algorithm here describes one class of dARTMAP networks. This system incorporates elements of the unsupervised dART model, as well as new features, including a content-addressable memory (CAM) rule for improved contrast control at the coding field. A dARTMAP system reduces to fuzzy ARTMAP when coding is winner-take-all. Simulations show that dARTMAP retains fuzzy ARTMAP accuracy while significantly improving memory compression.

Journal Article↗
PubMed2005

Effect of particle shape of active pharmaceutical ingredients prepared by fluidized-bed jet-milling on cohesiveness.

Milling is a common procedure to improve bioavailability of many active pharmaceutical ingredients (APIs), which typically have low solubility in water. But such micronization can yield an increase in the cohesiveness of particles. Although particle cohesiveness is desirable for tablet strength in the subsequent formulation process, increased particle cohesiveness can lead to operational difficulties in a milling equipment due to compaction of particles inside. In this article, the impact of milling via a fluidized-bed jet-mill on the cohesive strength and interparticle force was studied using Ethenzamide as a pharmaceutical model compound. As a result, the particle shape was found to affect both the tensile strength of powder bed and the interparticle cohesive force. A powder bed, having relatively high void fraction by direct tensile test, shows a positive correlation between the cohesive force and the particle sphericity, while powders with low void fraction by diametral compression test show a positive correlation between the cohesive force and the angularity of the particle.

Adhesives↗
PubMed2001

The spray drying of acetazolamide as method to modify crystal properties and to improve compression behaviour.

Acetazolamide shows a very poor compression ability and tablets must usually be produced through a wet granulation process. However, the possibility to obtain pure acetazolamide for direct compression could be interesting for industrial application. With the scope to obtain a material for direct compression, three different crystallisation methods were chosen, with respect to acetazolamide solvent solubility. (a) Acetazolamide was dissolved in an ammonia solution and then spray dried. It was possible to characterise the spherical particles as a mixture of two polymorphic forms, I and II by Powder X-ray diffraction study. (b) Pure form I was obtained by slowly cooling to room temperature a boiling water solution. (c) Pure form II, the marketed form, was obtained by neutralisation of an ammonia solution. Their compression behaviour was investigated firstly by a rotary press. Whilst pure polymorphic forms I and II could not be compressed, the spray dried particles showed very good compression properties. In fact, tablets were obtained only by spray dried particles, which show very good properties under compression and the absence of capping tendency. On the other hand, it was impossible to obtain tablets from polymorphic forms I and II, whatever compression pressures were used. In order to explain their densification mechanism, a single-punch tablet machine, equipped for the measurement of the upper punch displacement in the die, was used. From calculated Heckel's parameters, it was demonstrated that the spray dried material shows a greater particle rearrangement in the initial stage of compression due to its spherical habit and minor wrinkledness of particle surface. The crystalline structure due to the presence of polymorphic forms I and II concur to lowering the intrinsic elasticity of the material. This fact avoids the risk of the rupturing the interpaticulate bonds, which are formed during the compression, concurring to the consolidation of the tablet.

Acetazolamide↗