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At least 199 records · Page 11Linked to original sources

PubMed1987

Validation of closed-loop subcutaneous insulin infusion algorithm--application of subcutaneous insulin absorption kinetics.

For long-term glycemic normalization with a closed-loop control system, a subcutaneous insulin infusion algorithm has been developed based on the pharmacokinetics of subcutaneously administered insulin. A 3-compartmental model was applied to mathematically express the relation between the insulin injected subcutaneously as an input and the plasma insulin response as an output. A computer simulation study using this model showed that the following insulin infusion algorithm is feasible for closed-loop glycemic control by selecting appropriate parameters (Kp/Kd/Kc = 0.0056/0.92/-0.11), IIR(t) = Kp G(t)+Kd d G(t)/dt+Kc, where IIR(t) is the subcutaneous insulin infusion rate at time t (min), G(t) is the blood glucose concentration and Kp, Kd, Kc are the constants. In 5 pancreatectomized dogs, subcutaneous insulin infusion with this algorithm made it possible to keep postprandial glycemic levels after oral glucose load (2 g/kg) at 168 +/- 14 mg/dl (mean +/- SEM) in 60 min and maintained normoglycemia from 180 to 300 min with the total amount of infused insulin being 0.14 +/- 0.019 U/kg. In 5 insulin-dependent diabetic patients, the peaks of postprandial glycemic levels after meal load (450 kcal) were controlled to 176 +/- 36 mg/dl at 90 min and were reduced to 98 +/- 13 mg/dl at 300 min with the total amount of infused insulin being 0.172 +/- 0.063 U/kg. The mean peak plasma insulin level was 49 +/- 11 microU/ml at 90 min. These results indicate the clinical controllability of postprandial glycemia with the closed-loop subcutaneous insulin infusion algorithm in diabetic patients.

Algorithms↗

PubMed1988

A response algorithm for the low-pressure alarm condition.

A response algorithm consists of a logical sequence of maneuvers to be performed in response to a specific condition. With the advent of alarm-equipped monitors that alert anesthesiologists to the presence of potentially hazardous clinical conditions, a need has arisen to develop the corresponding alarm-oriented responses expected from anesthesiologists; this problem, however, has not been satisfactorily addressed in the literature. An algorithm is proposed that guides the anesthesiologist through the three limbs of the ventilation system--gas supply system, breathing circuit, and mechanical ventilator--in response to a low-pressure alarm condition during automatic mechanical ventilation. The three-limbed algorithm rapidly and efficiently localizes the likely cause of the low-pressure condition without compromising patient safety; in the event that the search for a cause is fruitless, a default mode of ventilation is employed. A discussion is provided of common causes (e.g., disconnections), alarm-defeating circumstances (false negatives), and potential algorithm-defeating situations (multiple faults).

Algorithms↗

PubMed1986

An algorithm for differential diagnosis in jaundice and its applications.

During the recent years a broad spectrum of diagnostic methods have appeared for the differentiation of obstructive and nonobstructive jaundice: ultrasound examination, CT-scan, direct cholangiography, etc. These investigations are costly and not without risks. It is therefore essential to devise an optimal diagnostic strategy for each patient. Extensive clinical and clinical chemical information was collected from 1,002 jaundiced patients. By application of Bayes' theorem and logistic discriminant analysis a diagnostic algorithm was developed based upon 21 variables of the 107 variables collected. This algorithm permitted a probabilistic classification of jaundiced patients into four diagnostic categories: acute non-obstructive, chronic non-obstructive, benign obstructive and malignant obstructive jaundice. Adopting a probability limit of 0.80, 683 patients (69 p. 100) were correctly classified, 34 patients (3.5 p. 100) were wrongly so, and 268 patients (27 p. 100) could not be classified with a probability above 0.80 (doubtful cases). The algorithm was also tested in a further series of 110 jaundiced patients and found to perform equally well: 88 patients classified, 22 patients remaining doubtful. Patients with doubtful diagnoses should be referred to a non-invasive test such as ultrasound examination, whereas patients with definite diagnoses can be referred to invasive tests (liver biopsy, direct cholangiography) as appropriate. The diagnostic algorithm seems to be a reliable tool for the primary differential diagnosis of the jaundiced patient and can be used in the planning of further diagnostic tests for the individual patient.

Algorithms↗

PubMed1995

An algorithmic approach to cancer pain management.

Pain and symptom management is an important aspect of hospice care. In an attempt to deliver consistent and high-quality interventions in a timely manner algorithms for pain and symptom management were developed. We have used these algorithms for the past 2 years with successful outcomes. Development of the pain and symptom management algorithms has contributed to the development of a standardized plan for symptom management. The algorithms offer the flexibility to respond to individual differences found in our patient population. Working together, physicians, nurses, and pharmacists offer a team approach to patient care.

Algorithms↗

PubMed1993

FLASH: a fast look-up algorithm for string homology.

A key issue in managing today's large amounts of genetic data is the availability of efficient, accurate, and selective techniques for detecting homologies (similarities) between newly discovered and already stored sequences. A common characteristic of today's most advanced algorithms, such as FASTA, BLAST, and BLAZE is the need to scan the contents of the entire database, in order to find one or more matches. This design decision results in either excessively long search times or, as is the case of BLAST, in a sharp trade-off between the achieved accuracy and the required amount of computation. The homology detection algorithm presented in this paper, on the other hand, is based on a probabilistic indexing framework. The algorithm requires minimal access to the database in order to determine matches. This minimal requirement is achieved by using the sequences of interest to generate a highly redundant number of very descriptive tuples; these tuples are subsequently used as indices in a table look-up paradigm. In addition to the description of the algorithm, theoretical and experimental results on the sensitivity and accuracy of the suggested approach are provided. The storage and computational requirements are described and the probability of correct matches and false alarms is derived. Sensitivity and accuracy are shown to be close to those of dynamic programming techniques. A prototype system has been implemented using the described ideas. It contains the full Swiss-Prot database rel 25 (10 MR) and the genome of E. Coli (2 MR). The system is currently being expanded to include the complete Genbank database.(ABSTRACT TRUNCATED AT 250 WORDS)

Algorithms↗

PubMed1994

Sequence comparisons via algorithmic mutual information.

One of the main problems in DNA and protein sequence comparisons is to decide whether observed similarity of two sequences should be explained by their relatedness or by mere presence of some shared internal structure, e.g., shared internal tandem repeats. The standard methods that are based on statistics or classical information theory can be used to discover either internal structure or mutual sequence similarity, but cannot take into account both. Consequently, currently used methods for sequence comparison employ "masking" techniques that simply eliminate sequences that exhibit internal repetitive structure prior to sequence comparisons. The "masking" approach precludes discovery of homologous sequences of moderate or low complexity, which abound at both DNA and protein levels. As a solution to this problem, we propose a general method that is based on algorithmic information theory and minimal length encoding. We show that algorithmic mutual information factors out the sequence similarity that is due to shared internal structure and thus enables discovery of truly related sequences. We extend that recently developed algorithmic significance method (Milosavljević & Jurka 1993) to show that significance depends exponentially on algorithmic mutual information.

Algorithms↗

PubMed1986

Self-stabilization of neuronal networks. I. The compensation algorithm for synaptogenesis.

Between the extreme views concerning ontogenesis (genetic vs. environmental determination), we use a moderate approach: a somehow pre-established neuronal model network reacts to activity deviations (reflecting input to be compensated), and stabilizes itself during a complex feed-back process. Morphogenesis is based on an algorithm formalizing the compensation theory of synaptogenesis (Wolff and Wagner 1983). This algorithm is applied to randomly connected McCulloch-Pitts networks that are able to maintain oscillations of their activity patterns over time. The algorithm can lead to networks which are morphogenetically stable but preserve self-maintained oscillations in activity. This is in contrast to most of the current models of synaptogenesis and synaptic modification based on Hebbian rules of plasticity. Hebbian networks are morphogenetically unstable without additional assumptions. The effects of compensation on structural and functional properties of the networks are described. It is concluded that the compensation theory of synaptogenesis can account for the development of morphogenetically stable neuronal networks out of randomly connected networks via selective stabilization and elimination of synapses. The logic of the compensation algorithm is based on experimental results. The present paper shows that the compensation theory can not only predict the behavior of synaptic populations (Wagner and Wolff, in preparation), but it can also describe the behavior of neurons interconnected in a network, with the resulting additional system properties. The neuronal interactions--leading to equilibrium in certain cases--are a self-organizing process in the sense that all decisions are performed on the individual cell level without knowing the overall network situation or goal.

Animals↗

PubMed1980

Comparison of two unsupervised algorithms.

The binary decision element described by the decision rule depending upon weight vector w is a model of neuron examined in this paper. The environment of the element is described by some unknown, stationary distribution (p(kappa). The input signals kappa[n] of the element appear in each step n independently in accordance with the distribution p(kappa). During an unsupervised learning process the weight vector w[n] is changed on the base of the input vector kappa[n]. In the paper there are regarded two self-learning algorithms which are stochastic approximation type. For both algorithms the same rule of past experiences neglecting or the rule of weight decrease has been introduced. The first algorithm differs from the other one by a rule of weight increase. It has been proved that only one of these algorithms always leads to the same decision rule in a given environment p(kappa).

Decision Making↗

PubMed1982

Frequency limitations of the two-point central difference differentiation algorithm.

A two-point central difference algorithm is often used to calculate the derivative of a function. This estimate is only valid over a limited frequency range. Therefore, the algorithm can be modeled as an ideal differentiator in series with a low-pass filter. The filter cutoff frequency is a function of the time between the points. We discuss the accuracy and limitations of using this algorithm on human saccadic eye movement data. To calculate the velocity of saccadic eye movements the algorithm should have a cutoff frequency of 74 Hz or above.

Eye Movements↗

PubMed1986

Consistency of assessment of adverse drug reactions in psychiatric hospitals: a comparison of an algorithmic and an empirical approach.

Within an ongoing drug surveillance project (AMUP) in psychiatric hospitals, a comparative study was carried out to evaluate two methods commonly used in the field of adverse drug reaction assessment. Two raters, who have cooperated with the project since its inception, evaluated 80 randomly selected ADRs twice; first, by an empirical (implicit) approach, and second, 4 weeks later, by using an algorithm as proposed by Kramer et al. 1979. Agreement on medication and related probability ratings was obtained in 81% of all 80 cases for the empirical method (weighted Kappa = 0.41), and in 69% for the algorithmic method (weighted Kappa = 0.62), indicating that agreement exceeded chance for both methods. By comparison with assessments made in previous case conferences of the project, empirical ratings were found to be reliable over time due to homogeneous use of criteria by project raters. In contrast to the reports on the subject, agreement between raters appeared to be superior in the empirical method as compared to the algorithmic assessment. Analysis of disagreements suggested that probability ratings based on the empirical method were nonspecific, due to conventional criteria applied in the project. Inter-rater agreement was reduced by polypharmacy, especially in the case of algorithmic assessments. The consistency of assessment was also lowered by the fact that the 2 methods assigned different weights to particular assessment criteria.

Drug-Related Side Effects and Adverse Reactions↗

PubMed1983

Efficient algorithms for searching for exact repetition of nucleotide sequences.

There are several algorithms designed for searches for homologous sequences (Fitch 1966; Needleman and Wunsch 1970; Chva'tal and Sankoff 1975; Griggs 1977; Sannkoff 1972; Smith and Waterman 1981; Smith et al. 1981, Wagner and Fischer 1974; Waterman et al. 1976). This paper presents some very simple and useful high speed, "text editing" algorithms that search for exact nucleotide sequence repetition and genome duplication. The last algorithm suggested here is specifically adapted for the 4-letter alphabet of nucleotide sequences. Owing to the rapid accumulation of nucleotide sequences and the frequent need to search for sequence repetition or where a given set of nucleotides occurs in long sequences, efficient algorithms of this type are a necessity.

Base Sequence↗

PubMed1985

An algorithm for monitoring sensory evoked potentials.

Brainstem auditory evoked potentials (BAEP) testing is used extensively to monitor auditory function during retromastoid craniectomies for microvascular decompression. The latency between BAEP peaks can change notably over a period of several seconds or minutes, a much shorter time than is necessary to acquire and analyze a conventionally averaged BAEP. This article describes a continuous monitoring algorithm that detects both large, rapid changes in waveform and slow changes in latency. A prestimulus control interval in the response data window provides a mechanism for evaluating the reliability of the response. The algorithm tracks the latency and amplitude of a selected peak, using several checks to avoid detecting the wrong peak. The tracking mechanism is simple yet effective and eliminates the need to suspend averaging for manual measurement of peak parameters. The peak latency and amplitude are displayed immediately. The algorithm indicates gross changes in the BAEP within 30 seconds and provides reliable data on latency trends. By increasing the frequency of acquiring new waveforms, the algorithm provides more immediate information for the surgeon.

Brain Stem↗

PubMed1985

A simple algorithm for defining the mean cardiac cycle of aortic flow and pressure during steady state.

A fast procedure for defining a cardiac cycle using simultaneously recorded and digitized aortic flow and pressure is presented. A simple algorithm, based on a double-threshold method, initially involves singling the dicrotic notch of flow in order to separate contiguous cardiac cycles during a given steady state. The individual cycles are carried back to a common origin of time, then they are normalized to the mean length and averaged. As a result of an averaging operation the algorithm gives a "mean cycle" of both pulsatile aortic pressure and flow. An "a posteriori" analysis of the noise components in the data has been carried out in order to justify the averaging operation. The "mean cycle" of aortic flow and pressure are suitable to be used as the input quantities of the automatic identification procedures recently assessed to estimate the parameters of simple models of the arterial input impedance. Our algorithm was defined and implemented as a FORTRAN program for a digital PDP 11/24 computer. This algorithm was tested by using pressure and flow data measured in the ascending aorta of dogs. About 26 sec were necessary to select 10 cardiac cycles (each one being about 200 samples long) of both flow and pressure in sequences of 2500 samples per signal and to compute the respective "mean cycles." Total peripheral resistance, total arterial compliance, and aortic characteristic impedance were estimated by aid of the simple three-element windkessel model. The results obtained by our method of determining parameters on the "mean cycle" of aortic pressure and flow were compared to the results obtained by averaging the parameters determined on each heart cycle.

Animals↗

PubMedDate not supplied

A parametric algorithm for computing model period and cohort human survival functions.

A parametric algorithm was developed for computing model cohort and period survival functions used in making projections of human populations. Two levels of parameters were used in developing the algorithm. The algorithm provides a method for calculating model period survival functions as a function of an expectation of life at birth; model cohort survival functions are calculated as a function of a time series of period expectations of life at birth. Expectations of life at birth ranging from about 35 to 110 years in both sexes may be accommodated by the algorithm.

Actuarial Analysis↗

PubMed1985

[Prediction of secondary structures of nucleic acids: algorithmic and physical aspects].

Prediction of secondary structures in nucleic acids requires both an adequate physical model and powerful calculation algorithms. In our approach, we cut the molecules in sections of which the contributions to the global energy are context-dependent but roughly additive. The structure of minimum energy is obtained by a tree search under constraints of binary incompatibilities. Our algorithm of the "incompatibility islets" is shown to be more powerful than the "bit parallel forward checking" algorithm, well known in Artificial Intelligence. Recurrent algorithms, proposed by other authors are even more rapid, but often miss the correct structures, for they demand a strict additivity of the energetic contributions, physically unjustified. New strategies, required to deal with molecules of more than 200 nucleotides are discussed. Our physical model has been improved by considering the special case of internal loops beginning with a G-A opposition. A bonus of 1.5 kcal. is attributed to such a feature, at each side of an internal loop. To illustrate our programs, we give the computed schemes for the 3' termini of the small subunit ribosomal RNA.

Base Sequence↗

PubMed1984

A new fast algorithm for the evaluation of regions of interest and statistical uncertainty in computed tomography.

A new algorithm for region of interest evaluation in computed tomography has been developed. Region of interest evaluation is a technique used to improve quantitation of the tomographic imaging process by summing (or averaging) the reconstructed quantity throughout a volume of particular significance. An important application of this procedure arises in the analysis of dynamic emission computed tomographic data, in which the uptake and clearance of radiotracers are used to determine the blood flow and/or physiologic function of tissue within the significant volume. The new algorithm replaces the conventional technique of repeated image reconstructions with one in which projected regions are convolved and then used to form multiple vector inner products with the raw tomographic data sets. Quantitation of regions of interest is made without the need for reconstruction of tomographic images. The computational advantage of the new algorithm over conventional methods is between a factor of 20 and a factor of 500 for typical applications encountered in medical science studies. The greatest benefit of the new algorithm (and the motivation for its development) is the ease with which the statistical uncertainty of the result is computed. The entire covariance matrix for the evaluation of regions of interest can be calculated with relatively few operations.

Computers↗

PubMed1982

The clinical usefulness of an algorithm for the interpretation of biochemical profiles with hypercalcemia.

A logical, systematic approach to the interpretation of diagnostic biochemical profiles in patients with hypercalcemia has been attempted through the use of algorithms (decision trees). A tentative algorithm (ALG-I) and an expanded and modified version (ALG-II) were compared for effectiveness in tests of 80 patients with hypercalcemia at Charity Hospital in New Orleans. The overwhelming majority (69%) of these patients had malignant disease. Comparative performance indicated that the modified algorithm (ALG-II) assigned the correct diagnostic categories in 66% of cases, compared with 53% for ALG-I, but the clinical performance of ALG-I improved (agreement rate of 60%) when it was assumed that patients with malignancy could have coexisting hyperparathyroidism or pseudohyperparathyroidism. The clinical trial indicated that both algorithms were fairly comparable and that their primary use would be as teaching aids for medical students and residents to suggest various diagnostic possibilities for hypercalcemia in patients.

Adolescent↗

PubMedDate not supplied

Toward an automated analysis system for nuclear magnetic resonance imaging. II. Initial segmentation algorithm.

Image segmentation algorithms based on hierarchical clustering have been developed for analysis of T1 and T2 nuclear magnetic resonance images. Application of these algorithms to simultaneous T1-T2 images of healthy volunteers extracted fundamental tissue types in the brain. These algorithms also were used both to identify the extent of the region of involvement of a subject with a history of a grade 3 astrocytoma of the right frontal lobe of the brain, and to characterize the tissue within the region of involvement. These results suggest that a simple segmentation algorithm can produce reasonable clustering of tissue types within the brain.

Biometry↗