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Prediction of protein helices with a derivative of the strip-of-helix hydrophobicity algorithm.

The strip-of-helix hydrophobicity algorithm was devised to identify protein sequences which, when coiled as alpha or 3(10) helices, had one axial, hydrophobic strip and otherwise variably hydrophilic residues. The strip-of-helix hydrophobicity algorithm also ranked such sequences according to an index, the mean hydrophobicity of amino acids in the axial strip. This algorithm well predicted T cell-presented fragments of antigenic proteins. A derivative of this algorithm (the structural helices algorithm (SHA] was tested for the prediction of helices in crystallographically defined proteins. For the SHA, eight amino acid sequences, 2 cycles plus one amino acid in an alpha helix, with strip-of-helix hydrophobicity indices greater than 2.5, were selected with overlapping segments joined. These selections were terminated according to simple "capping rules," which took into account the roles of N-terminal Asn or Pro and C-terminal Gly in the stability of helices. In analyses of 35 crystallographically defined proteins with known alpha and 3(10) helices, the predictions with the SHA overlapped (had overlap indices x greater than or equal to 0.5) with 34% of known helices, touched (had overlap indices 0.5 greater than x greater than 0) or overlapped with 66% of known helices, or were neighboring (came within 6 residues) or touched or overlapped with 82% of known helices. At each level of judging the quality of prediction, the SHA was usually less sensitive (correct predictions/total number of known helices) and more efficient (correct predictions/total number of predictions) than the Chou-Fasman and Garnier-Robson methods. It was simpler in design and calculation. The chemical mechanisms underlying these algorithms appear to apply both to protein folding and to selection of T cell-presented antigenic sequences.

Algorithms

[Development of clinical algorithms for quality assurance in management of multiple trauma].

Resuscitation and management of high-risk multiple trauma patients require a systematic and coordinated approach to diagnostic and therapeutic interventions. Clinical algorithms with branch chain decision logic can provide a clear and organized transformation of clinical standards for trauma care. Owing to their capability in formalization and standardization, algorithms define precisely the process of care and serve as a central interface within the system of quality assurance and quality control. The standardized document symbols and conventions for information processing according to ANSI/ISO/CCITT regulations are generally applied to the flowchart design of clinical algorithms. Special starting and ending point symbols make it possible to break down complex processes in several single interrelated algorithms. Inclusion of optional criteria checklists reduces the number of decision nodes and loops and minimizes the extent of a comprehensive algorithm. Clinical algorithms are an excellent tool for converting highly complex concepts of multiple trauma management into a logical, prioritized and systematic process of care.

Algorithms

[Verification of accuracy of several algorithms to quantitate left ventricular regional wall motion: a study using cine MR imaging with myocardial tagging].

To verify the accuracy of several algorithms used to quantitate left ventricular (LV) regional wall motion, five volunteers were examined by cine MR imaging with presaturation myocardial tagging in short-axis and 4-chamber sections. Three algorithms for the wall motion analysis, radial, centerline, and originally developed "modified-Hildreth" methods, were applied to the cine MR images, and dissociation of the end-systolic position of the tags estimated by each algorithm from the true position was examined. The modified-Hildreth method was comparable in accuracy to the other methods for estimating end-systolic tag position. Significantly worse estimation of the tag position by the three algorithms occurred in the 4-chamber section compared with the short-axis section (p < 0.001, 0.005), indicating difficulties in the wall motion analysis of "long-axis" LV images. Among the algorithms, the centerline method showed the highest accuracy of the estimation in the 4-chamber section, and the modified-Hildreth method was the best in the short-axis section. In the 4-chamber section, correction of the position of end-diastolic and end-systolic images around the luminal centroids improved the estimation (p < 0.01, 0.05). Tagging cine MR imaging was proved to be useful for determining the most suitable algorithm for quantitative wall motion analysis of LV images obtained from conventional angiocardiography and other imaging modalities.

Adult

A modified EM algorithm for estimation in generalized mixed models.

Application of the EM algorithm for estimation in the generalized mixed model has been largely unsuccessful because the E-step cannot be determined in most instances. The E-step computes the conditional expectation of the complete data log-likelihood and when the random effect distribution is normal, this expectation remains an intractable integral. The problem can be approached by numerical or analytic approximations; however, the computational burden imposed by numerical integration methods and the absence of an accurate analytic approximation have limited the use of the EM algorithm. In this paper, Laplace's method is adapted for analytic approximation within the E-step. The proposed algorithm is computationally straightforward and retains much of the conceptual simplicity of the conventional EM algorithm, although the usual convergence properties are not guaranteed. The proposed algorithm accommodates multiple random factors and random effect distributions besides the normal, e.g., the log-gamma distribution. Parameter estimates obtained for several data sets and through simulation show that this modified EM algorithm compares favorably with other generalized mixed model methods.

Algorithms

Identification and estimation algorithm for stochastic neural system.

An algorithm for the estimation of stochastic processes in a neural system is presented. This process is defined here as the continuous stochastic process reflecting the dynamics of the neural system which has some inputs and generates output spike trains. The algorithm proposed here is to identify the system parameters and then estimate the stochastic process called neural system process here. These procedures carried out on the basis of the output spike trains which are supposed to be the data observed in the randomly missing way by the threshold time function in the neural system. The algorithm is constructed with the well-known Kalman filters and realizes the estimation of the neural system process by cooperating with the algorithm for the parameter estimation of the threshold time function presented previously (Nakao et al., 1983). The performance of the algorithm is examined by applying it to the various spike trains simulated by some artificial models and also to the neural spike trains recorded in cat's optic tract fibers. The results in these applications are thought to prove the effectiveness of the algorithm proposed here to some extent. Such attempts, we think, will serve to improve the characterizing and modelling techniques of the stochastic neural systems.

Animals

Analysis of a cooperative stereo algorithm.

Marr and Poggio (1976) recently described a cooperative algorithm that solves the correspondence problem for stereopsis. This article uses a probabilistic technique to analyze the convergence of that algorithm, and derives the conditions governing the stability of the solution state. The actual results of applying the algorithm to random-dot stereograms are compared with the probabilistic analysis. A satisfactory mathematical analysis of the asymptotic behaviour of the algorithm is possible for a suitable choice of the parameter values and loading rules, and again the actual performance of the algorithm under these conditions is compared with the theoretical predictions. Finally, some problems raised by the analysis of this type of "cooperative" algorithm are briefly discussed.

Depth Perception

Sensitivity and specificity of a dual-chamber arrhythmia recognition algorithm for implantable devices.

Present ventricular rate-based arrhythmia detection algorithms lack specificity. Using a training set of 109 endocardial electrogram recordings, a sensitive and specific dual-chamber arrhythmia recognition algorithm has been developed. The algorithm uses atrial and ventricular rates, irregularity, degree of beat-to-beat similarity, and measure of electrogram complex distinctiveness to arrive at a diagnostic conclusion. A test set of 121 endocardial electrogram recordings obtained during provocative electrophysiology studies was then used for blinded validation of the algorithm. In normal rhythm, 1:1 tachycardia, atrial tachycardia, atrial flutter, atrial fibrillation, ventricular tachycardia, and ventricular fibrillation, the percentages of sensitivity/specificity were, respectively, 100/99, 100/99, 80/99, 89/98, 91/97, 92/100, and 100/98. Although ventricular rate alone can usually distinguish normal rhythm, ventricular tachycardia, and ventricular fibrillation, it is confounded by atrial arrhythmias and 1:1 tachycardias. When tested on a database, a ventricular rate-only algorithm resulted in sensitivity/specificity of 100/65, 90/78, and 100/99%, respectively, for these three rhythms. Therefore, the dual-chamber algorithm based on both temporal and morphologic measures provides better distinction of normal rhythm and ventricular tachycardia than existing methods, without sacrificing sensitivity.

Arrhythmias, Cardiac

Potential effect of self-care algorithms on the number of physician visits.

To assess the potential effect of self-care algorithms on the number of physician visits, actual visits from the Seattle Virus Watch were compared retrospectively with those recommended by clinical algorithms for common illnesses from the book, Take Care of Yourself, by Vickery and Fries. From a total of 3929 illnesses, records indicating the presence of the index symptom for eight algorithms were identified, determining whether the criteria for seeing a physician were met and whether a physician visit was recorded. The number of visits observed was compared to the number of visits recommended by the algorithms. Strict adherence would have increased the number of visits over that observed for five, remained the same for two, and decreased for one of the algorithms. These results indicate that adherence to some commonly promulgated self-care algorithms may increase rather than decrease the number of physician visits.

Activities of Daily Living

Clinical algorithms for prehospital cardiac care.

Algorithms for the prehospital management of cardiac arrhythmias were developed and their use by and value to paramedics evaluated. The algorithms, in booklet form, were distributed to half of the Philadelphia paramedic platoons; paramedics in the other platoons followed a narrative protocol that reflected identical contents. An arrhythmia recognition test given 18 months after the algorithm booklets were introduced showed that paramedics who received the booklets scored significantly higher in identifying life-threatening arrhythmias (p = 0.029) than did their counterparts without the booklets. Survival data for 459 patients in ventricular fibrillation treated by paramedics were collected 1 year before and 7 months after the introduction of the algorithm booklets. The paramedics using the algorithms improved their survival rate from 11.25 to 15.1 per cent, while the survival rate for patients treated by paramedics using the narrative protocols decreased from 12.4 to 7.7 per cent. The likelihood of obtaining a ratio of survival odds of this magnitude when there is no true difference is 0.092. Time-to-death was significantly different (p = 0.04) for the two groups of patients. Thus, the use of algorithm booklets as an inexpensive educational aid for paramedics is recommended.

Allied Health Personnel

The use of a computerized algorithm to determine single cardiac cell volumes.

Single cardiac muscles cell volume data have been difficult to obtain, especially because the shape of a cell is quite complex. With the aid of a surface reconstruction method, a cell volume estimation algorithm has been developed that can be used on serial of cells. The cell surface is reconstructed by means of triangular tiles so that the cell is represented as a polyhedron. When this algorithm was tested on computer generated surfaces of a known volume, the difference was less than 1.6%. Serial sections of two phantoms of a known volume were also reconstructed and a comparison of the mathematically derived volumes and the computed volume estimations gave a per cent difference of between 2.8% and 4.1%. Finally cell volumes derived using conventional methods and volumes calculated using the algorithm were compared. The mean atrial muscle cell volume derived using conventional methods was 7752.7 +/- 644.7 micrometers3, while the mean computerized algorithm estimated atrial muscle cell volume was 7110.6 +/- 625.5 micrometers3. For AV bundle cells the mean cell volume obtained by conventional methods was 484.4 +/- 88.8 micrometers3 and the volume derived from the computer algorithm was 506.0 +/- 78.5 micrometers3. The differences between the volumes calculated using conventional methods and the algorithm were not significantly different.

Animals

In vivo comparison of different algorithms for the artificial beta-cell.

Using an extracorporeal artificial beta-cell in chronically diabetic dogs, the effects of four different mathematical models of glucose-controlled insulin dosage were compared: the Biostator algorithm (quadratic equation), Toronto algorithm (hyperbolic tangent function), Karlsburg algorithm (modified first-order derivative controller), and Ilmenau algorithm (second-order linear difference equation). The constants of all formulas implemented for the artificial beta-cell were obtained by regression analysis of paired blood glucose and plasma insulin data from normal control animals. Thus, they were biologically equivalent for all formulas. The patterns of blood glucose, insulin doses, and plasma insulin before, during, and after an intravenous glucose infusion test performed during the glucose-controlled insulin infusion showed no significant differences between the experimental groups subjected to the different algorithms. However, in no case were really normal blood glucose response curves restored by the artificial beta-cell. This might be due, first, to the fact that the algorithm parameters were not adapted to the actual individual insulin responsiveness, second, to the unphysiological peripheral venous route of insulin administration, and, third, to the lack of appropriate adaptation of the animals to normoglycemia.

Animals

Two-film brachytherapy reconstruction algorithm.

We have developed a new isocentric two-film reconstruction algorithm for brachytherapy seed and needle implants. The algorithm has no requirements that the two films be orthogonal, symmetric, or even be taken in a transverse plane. In addition, there is no requirement that the two films even have the same number of images. We have found removal of these usual constraints useful for head and neck implants where images are often obscured by patient anatomy. The inherent image matching ambiguities associated with traditional two-film techniques are minimized by considering the image end points, rather than just the image centroids. For two films, the new algorithm, which considers all image combinations at one time, matches all the end-point images on one film with those on the other, and then reconstructs the end-point positions of the seeds. The algorithm minimizes the difference between the actual images and the projected images from the reconstructed seeds. The new two-film image matching problem is shown to be equivalent to the well-known assignment problem. For an implant of N seeds, this equivalence allows the two-film problem to be solved by an algorithm (ACM algorithm 548) that scales with a polynomial power of N, rather than N! as is usually assumed. An implant of N seeds can be matched and reconstructed in approximately (N/20)2s on a VAX 11/780.

Brachytherapy

An excitation-pattern algorithm for the estimation of (2f1-f2) and (f2-f1) cancellation level and phase.

An excitation-pattern algorithm is described which provides an estimate of cancellation level and phase for the (2f1-f2) and (f2-f1) distortion products. An experiment is first conducted to demonstrate the need for such an algorithm for (f2-f1) level predictions. The results of this experiment, which employed three pairs of primaries having complementary input levels (L1 = 65, L2 = 85 dB; L1 = 85, L2 = 65 dB), do not agree with the predictions of another similar algorithm [E. Zwicker, J. Acoust. Soc. Am. 69, 1410-1413 (1981)]. A new excitation-pattern algorithm is then described. The predicted level behavior for (f2-f1) and (2f1-f2) is more accurate for the proposed algorithm. In addition, an accurate phase estimate is also provided by the new algorithm.

Acoustic Stimulation

Future promise, current clinical ambiguity: a systematic review of machine learning algorithm outputs predicting risk of cardiovascular disease.

OBJECTIVE: To examine whether the outputs of machine learning algorithms designed to predict risk of cardiovascular disease (CVD) address known deficiencies of the Framingham Risk Score (FRS) and improve risk estimates. METHODS: For this critical review, Medline, Embase and IEEE were searched from inception to 1 January 2025. Included were studies describing machine learning algorithms designed to specifically compare output of cardiovascular risk assessment with the FRS. Commentaries, letters, unpublished work or non-peer-reviewed papers were excluded.Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, two reviewers screened titles and abstracts independently, then populated a purpose-built data extraction form. A subsequent qualitative thematic analysis focused on algorithms' strengths, added value, potential harms, unintended consequences and equity implications.The main outcome assessed was whether, among healthy adults, the algorithm improved CVD risk prediction relative to the FRS. RESULTS: Of 707 studies retrieved, 29 met inclusion criteria. 23 reported improved predictive ability relative to the FRS. Most datasets and/or medical records used included sociodemographic predictors of CVD not included among FRS inputs. Some added costly diagnostic tests like CT angiography to FRS screening indicators. When they were defined, inputs and outcomes such as hypertension or myocardial infarction did not always adhere to FRS values. Statistical significance was generally taken as a proxy for clinical significance. Some algorithms overestimated the number at risk compared with the FRS without discussing whether that larger proportion might be at risk of overdiagnosis rather than CVD, while a few decreased the proportion found to be at risk. CONCLUSIONS: Use of artificial intelligence to improve accuracy of risk assessment for CVD demonstrates the technological capacity to merge known sociodemographic predictors with biologic variables and examine non-linear interactions among these. Still needed to achieve patient benefit is clinical insight, adherence to screening principles and cost-benefit assessment of inputs selected.

Humans

A fast spot segmentation algorithm for two-dimensional gel electrophoresis analysis.

An important issue in the automation of two-dimensional gel electrophoresis image analysis is the detection and quantification of protein spots. A spot segmentation algorithm must detect, define the extent of, and measure the integrated density of spots under a wide variety of actual gel image conditions. Besides these functions, the algorithm must be memory efficient to be able to process very large gel images and do this in a reasonable amount of computation time on low-cost computers, such as workstations and personal computers. We have developed a fast spot segmentation algorithm, extending the GELLAB-II segmenter, which extracts spots in a single raster scanning pass through the gel image. The performance analysis of the algorithm will be given in the paper as well as a discussion of the algorithm.

Algorithms

Efficient algorithms for generating interpolated (zoomed) MR images.

This paper discusses the two-dimensional implementation of a number of modified fast Fourier transform (FFT) algorithms that efficiently interpolate (zoom) magnetic resonance (MR) images. If the original image was sampled at a rate satisfying the Nyquist criterion, these algorithms would effectively increase the sampling rate, permitting image details to be more easily discerned. The Skinner interpolating fast Fourier transform (SIFFT) avoids many of the computationally unnecessary complex multiplications that occur when interpolating using the normal fast Fourier transform algorithm. The novel interpolating fast Fourier transform (NIFFT) offers further savings when a subimage is required. Theoretical and experimental timings that compare the use of the normal FFT, SIFFT, and NIFFT algorithms for interpolation are given using magnetic resonance image reconstruction examples. Time savings of a factor of 2 to 4 are possible in typical experimental situations. Time savings of factors of 5 to 20 are possible when zooming images using two-dimensional band selectable digital filtering (2D-BSDF) in combination with decimation and the SIFFT algorithm. In 2D-BSDF, the original MRI data set is reduced in size to retain only those frequency components corresponding to a desired subimage, thereby decreasing the computational load associated with further processing. A significant reduction in computation time is achieved when modeling is combined with 2D-BSDF and SIFFT as fewer points require modeling.

Algorithms

The diminishing variance algorithm for real-time reduction of motion artifacts in MRI.

A technique has been developed whereby motion can be detected in real time during the acquisition of data. This enables the implementation of several algorithms to reduce or eliminate motion effects from an image as it is being acquired. One such algorithm previously described is the acceptance/rejection method. This paper deals with another real-time algorithm called the diminishing variance algorithm (DVA). With this method, a complete set of preliminary data is acquired along with information about the relative motion position of each frame of data. After all the preliminary data are acquired, the position information is used to determine which data frames are most corrupted by motion. Frames of data are then reacquired, starting with the most corrupted one. The position information is continually updated in an iterative process; therefore, each subsequent reacquisition is always done on the worst frame of data. The algorithm has been implemented on several different types of sequences. Preliminary in vivo studies indicate that motion artifacts are dramatically reduced.

Algorithms

Algorithms for extracting motion information from navigator echoes.

Algorithms to reliably detect motion in navigator echoes are crucial to many MRI motion suppression techniques. The accuracy of these algorithms is affected by noise and deformation of navigator echo profile caused by physiologic motion. This study compared the performance of algorithms based on correlation and least squares for extracting displacement information from motion-monitoring navigator echoes, using computer simulation and in vivo imaging. The least squares algorithm was determined to be of higher accuracy than the correlation algorithm against errors caused by noise and profile deformation.

Algorithms