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PubMed1999

Algorithm for assessment of the oxygen, acid-base and electrolyte status (ALBOA BEACH).

To achieve accurate interpretation of blood gas analysis data in intensive care units, the oxygen, acid-base and electrolyte-metabolite profile of arterial blood should be comprehensively and adequately monitored and assessed. A number of diagnostic software programmes have been developed to assist clinicians in this and to help improve instruction in this field. In the present study we describe an algorithm and a programme for assessment of the oxygen, acid-base and electrolyte status of the arterial blood. The algorithm, as well as the software programme, is named ALBOA BEACH, which is an acronym of the programme's full name--ALgorithm for Blood Oxygen, Acid-Base, Electrolyte And respective CHarts. The algorithm takes account of the latest achievements in blood-gas analysis; it can be used both in on-line and off-line modes and is useful in the laboratory and pathophysiological assessment of blood-gas disorders. The algorithm is based on a rigorous pathophysiological analysis and the interpretation achieved as a result is much more accurate than usual. Thus it provides a most reliable basis for taking the right clinical decision and making the proper prognosis of the possible critical conditions. The algorithm also provides additional bases for interpretations of data in the borderline zones, with due warnings in cases of absence of physiological coherence between the various parameters and modules. The programme is designed to be used with the modern multifunctional blood-gas analysers; it can be of assistance in making diagnoses, in the training and research activity in the intensive care units and specialised blood gas laboratories.

Acid-Base Equilibrium↗

PubMed2001

A mini-greedy algorithm for faster structural RNA stem-loop search.

When a set of coregulated genes share a common structural RNA motif, e.g. a hairpin, most motif search approaches fail to locate the covarying but structurally conserved motif. There do exist methods that can locate structural RNA motifs, like FOLDALIGN, but the main problem with these methods is that they are computationally expensive. In FOLDALIGN, a major contribution to this is the use of a greedy algorithm to construct the multiple alignment. To ensure good quality many redundant computations must be made. However, by applying the greedy algorithm on a carefully selected subset of sequences, near full greedy quality can be obtained. The basic idea is to estimate the order in which the sequences entered a good greedy alignment. If such a ranking, found from all pairwise alignments, is in good agreement with the order of appearance in the multiple alignment, the core structural motif can be found by performing the greedy algorithm on just the top sequences in the ranking. The ranking used in this mini-greedy algorithm is found by using two complementing approaches: 1) When interpreting the FOLDALIGN score as an inner product (kernel), the sequences can be ranked according to their distance to their center of mass; 2) We construct an algorithm that attempts to find the K closest sequences in the vector space associated with the inner product, and the remaining sequences can be ranked by their minimum distance to any of the sequences, or to the center of mass in this set. The two approaches arecompared and merged, and the results discussed. We also show that structural alignments of near full greedy quality can found in significantly reduced time, using these methods. The algorithm is being included in the SLASH (Stem-Loop Align SearcH) server available at http://www.bioinf.au.dk/slash.

Algorithms↗

PubMed2002

[Comparison of parameter optimization algorithms for environmental model].

Parameters identification is achieved through the minimization of objective function based on model outputs and the observed data. Because of ever increasing complexity of environmental-models, there are significant difficulty for conventional optimal methods to present a global optimization. On the contrast, however, direct optimization algorithms are widely developed in recent years due to increasing computer efficiency and show promising applications. Four direct optimal algorithms, i.e. CRS algorithm, SCE UA algorithm, SA algorithm and Annealing-Simplex algorithm, were thus selected in this paper to compare their performances via case studies.

Algorithms↗

PubMed2002

Validation of the urgency algorithm for near-side crashes.

The URGENCY algorithm uses vehicle crash sensor data in Automatic Crash Notification (ACN) systems to assist in instantly identifying crashes that are most likely to have time critical injuries. The algorithm also provides the capability of improving injury identification, using data obtained from the scene. The prime purpose of the algorithm is to automatically provide emergency medical responders with objective information on crash severity to assist in detecting the approximately 1% of crashes with serious injuries needing the most urgent medical care. The algorithm calculates the risk of a MAIS 3+ injury being present in the crashed vehicle, instantly at the time of the crash. The prediction can be subsequently updated as more information becomes available. The algorithm was based on a multiple regression analysis using data from the National Accident Sampling System/Crashworthiness Data System, (NASS/CDS) years 1988-95. In this paper, the accuracy of the algorithm was evaluated for near side crashes by applying it retrospectively to the population of injured occupants in NASS 1997-2000. URGENCY was applied to the population of injured occupants in near side crashes. Using an injury risk criterion of 50%, URGENCY identified 69% of the crashes with MAIS 3+ injuries. By lowering injury risk criterion to 40%, URGENCY identified 78% of the crashes with MAIS 3+ injuries. Vehicle side intrusion was found to be a highly influential variable. By changing side intrusion from a binary to a continuous variable, the correctly identified crashes increased from 69% to 81%. Examination of the consequence of missing variables found that unknown values of occupant height and weight had a negligible effect on the ability to capture the MAIS 3+ injured. However, lack of knowledge of these variables did increase the magnitude of the false positives.

Accidents, Traffic↗

PubMed2002

Algorithms in clinical psychiatry: a stepped approach toward the path to recovery.

The use of clinical practice guidelines and treatment algorithms has become increasingly prevalent across all fields of medicine. The Texas Medication Algorithm Project has developed algorithms for major depressive disorder to facilitate clinical decision-making by providing physicians with a detailed, yet concise, summary of current clinical data on available pharmacotherapeutic interventions, together with specific treatment strategies and tactical recommendations. The goal of the algorithm is the attainment of full and sustainable remission of symptoms. Clinical experts, practitioners, and administrators, as well as patients and their families, all contributed to the formulation and implementation of the algorithm in order to ensure an optimum level of effectiveness and practicality. It is hoped that algorithm-driven pharmacotherapy of depression will increase the quality of care, leading to improved patient outcomes, reducing unnecessary practice variation, and increasing the overall cost-effectiveness of treatment intervention.

Algorithms↗

PubMed1998

[Implementing a relatively rigorous algorithm of dynamic EIT problem on the modified FEM model].

We deduced a relatively rigorous algorithm of dynamic EIT problem-general inverse algorithm, and implemented it on the computer FEM model. Images which can show the changing of the resistivity(i.e. dynamic resistivity images) were gained. Also we modified the ordinary FEM model according to the characteristic of the EIT problem and implemented the general inverse algorithm on the modified model. The ill-posed condition of the forward matrix based on the modified model was fairly improved. It can be seen from the results that the general inverse algorithm with modified FEM model is an algorithm better than the back-projection algorithm in terms of object locating, image definition, and the ability of dealing with complex object and noise.

Algorithms↗

PubMed2003

Algorithms for multiple genome rearrangement by signed reversals.

We discuss a multiple genome rearrangement problem by signed reversals: Given a collection of genomes, we generate them in the minimum number of signed reversals. It is NP-hard and equivalent to finding an optimal Steiner tree to connect the genomes by reversal paths. We design two algorithms to find the optimal Steiner nodes of the problem: Neighbor-perturbing algorithm and branch-and-bound algorithm. The first one is a polynomial running time approximation algorithm. It searches for the optimal Steiner nodes by perturbing initial Steiner nodes nearby their neighborhoods and improving them better and better until convergence. The second one is an exact exponential running time algorithm for a median problem. It finds the optimal Steiner node by checking all candidates that satisfy the necessary conditions for optimal Steiner nodes. We implement the algorithms into two programs respectively and show by experimental examples that they are more efficient than other similar ones, such as GRAPPA, BPAnalysis, and MGR, etc.

Algorithms↗

PubMed2003

Porcine model of diabetic dyslipidemia: insulin and feed algorithms for mimicking diabetes mellitus in humans.

A weakness of many animal models of diabetes mellitus is the failure to use insulin therapy, which typically results in severe body wasting. Data collected from such studies must be interpreted cautiously to separate the effects of hyperglycemia from those of starvation. We provide several algorithms that were used by us in two long-term (20-week) experiments in which hyperglycemia (300 to 400 mg/dl), dyslipidemia (cholesterol [280 to 405 mg/dl] and triglycerides [55 to 106 mg/dl] concentrations), and positive energy balance were maintained in swine. Yucatan miniature swine groups included control, alloxan-induced diabetes mellitus, diabetes mellitus plus diet-induced dyslipidemia, and exercise-trained diabetic dyslipidemic pigs. The algorithms were developed for the porcine model because of several similarities to humans, including: cardiac anatomy and physiology, propensity for sedentary behavior, and metabolism of dietary carbohydrates and lipids. Acute toxic effects of alloxan (hypoglycemia, hyperglycemia, nephrotoxicosis) were minimized by preventive fluid loading and by use of algorithms in which insulin, food, and fluid therapy were administered. Long-term insulin and food maintenance algorithms elicited normal body weight gain in all three diabetic groups (lean experiment) and threefold greater body weight gain in pigs of an obesity experiment. Exercise-trained pigs of both experiments manifested significantly increased work performance and did not experience medical complications. We conclude that these algorithms can be used in swine, or similar algorithms can be developed for other animal species to maintain hyperglycemia and/or dyslipidemia, while avoiding diabetes-induced wasting. Importantly, animal models of diabetes mellitus that maintain positive energy balance and poor glycemic control provide a marked improvement over other models by more closely mimicking the human presentation of diabetes mellitus.

Algorithms↗

PubMed2003

[Image reconstruction in electrical impedance tomography based on genetic algorithm].

Image reconstruction in electrical impedance tomography (EIT) is a highly ill-posed, non-linear inverse problem. The modified Newton-Raphson (MNR) iteration algorithm is deduced from the strictest theoretic analysis. It is an optimization algorithm based on minimizing the object function. The MNR algorithm with regularization technique is usually not stable, due to the serious image reconstruction model error and measurement noise. So the reconstruction precision is not high when used in static EIT. A new static image reconstruction method for EIT based on genetic algorithm (GA-EIT) is proposed in this paper. The experimental results indicate that the performance (including stability, the precision and space resolution in reconstructing the static EIT image) of the GA-EIT algorithm is better than that of the MNR algorithm.

Algorithms↗

PubMed1992

An annotated algorithm approach to clinical guideline development.

The Urinary Incontinence in Adults Guideline Panel facilitated the ready elucidation of its guideline's management recommendations through the use of an annotated algorithm approach. The algorithms created as part of this guideline differ from previous algorithms in two ways: (1) they employ systematic annotation to link explicitly the algorithms' recommendations to the literature, and (2) they contain patient counseling and decision nodes to depict the major preference-dependent decision or branch points in the algorithm. We believe that these two innovations can help ensure the clinical validity of guidelines' algorithms while preserving appropriate clinical flexibility and respecting patient preferences.

Algorithms↗

PubMed1991

Exploring a new best information algorithm for Iliad.

Iliad is a diagnostic expert system for internal medicine. One important feature that Iliad offers is the ability to analyze a particular patient case and to determine the most cost-effective method for pursuing the work-up. Iliad's current "best information" algorithm has not been previously validated and compared to other potential algorithms. Therefore, this paper presents a comparison of four new algorithms to the current algorithm. The basis for this comparison was eighteen "vignette" cases derived from real patient cases from the University of Utah Medical Center. The results indicated that the current algorithm can be significantly improved. More promising algorithms are suggested for future investigation.

Algorithms↗

PubMed1991

Stochastic simulation algorithms for query networks.

One of the barriers to using belief networks for medical information retrieval is the computational cost of reasoning as the networks become large. Stochastic simulation algorithms allow one to compute approximations of probability values in a reasonable amount of time. We previously examined the performance of five stochastic simulation algorithms applied to four simple belief networks networks and found that the Self-Importance algorithm performed well. In this paper, we examine how the same five algorithms perform when applied to a belief network derived from the cardiovascular subtree of the Medical Subject Headings (MeSH). Both the Likelihood Weighting and Self-Importance algorithms perform well when applied to the MeSH-derived network, suggesting that stochastic simulation algorithms may provide reasonable performance in medical information retrieval settings.

Algorithms↗

PubMed1991

Use of immunoglobulin heavy-chain and light-chain measurements in a multicenter trial to investigate monoclonal components: II. Classification by use of computer-based algorithms.

We describe a computer algorithm for classifying serum monoclonal proteins (MC) based on serum protein electrophoresis (SPE) and the automated measurement of kappa and lambda light chains and IgG, IgA, and IgM. We developed the algorithm by using a large database of unselected samples containing MC collected in a multicenter study. The performance of the algorithm was optimized by using iterative computational procedures and was tested on both the development database and on an independent set of MC-containing samples. With the development database, the algorithm correctly classified 50% and misassigned 2.5% of the MC. Where the MC were present in concentrations greater than 10 g/L, the rate of successful classification increased to 72% with 3% misclassification. When the algorithm was tested on a group of 101 MC-containing samples from an independent source, 67% were correctly classified and 8% misclassified, half of the latter being unusual IgD myelomas. We discuss the scope for the application of the algorithm in routine laboratory practice involving personal computer software.

Algorithms↗

PubMed1991

Algorithm to predict triple-vessel/left main coronary artery disease in patients without myocardial infarction. An international cross validation.

Logistic regression was applied to the clinical, risk factor, and exercise data of consecutive angiographic referrals without prior myocardial infarction to determine an algorithm predicting the probability of triple-vessel/left main coronary artery disease. These data were obtained from a total of 1,074 such subjects from patient populations at four centers (Cleveland Clinic Foundation, Cleveland, Ohio; Hungarian Institute of Cardiology, Budapest, Hungary; the university hospitals, Zurich and Basel, Switzerland; and the Veterans Administration Medical Center, Long Beach, Calif.) and used to derive four separate probability algorithms. Each algorithm is based on patient data from study samples at three of the four centers and consists of 272 logistic functions, which are related to linear combinations of 13 variables (age, sex, type of chest pain, systolic blood pressure, resting electrocardiogram, serum cholesterol, fasting blood sugar, achieved exercise work load, achieved heart rate, exercise-induced angina and hypotension, heart rate-adjusted resting ST depression, and exercise ST slope). The four algorithms were cross validated by testing them on the populations not involved in their derivation. The resulting probabilities in the four test groups were then compared with the angiographic findings of triple-vessel/left main coronary artery disease. The discriminatory power of all the algorithms was fair to good (area under receiver operating characteristic curve, 0.68, 0.75, 0.82, 0.85) in the test groups. The algorithm did not significantly underestimate or overestimate disease probability except in one center (Long Beach).(ABSTRACT TRUNCATED AT 250 WORDS)

Algorithms↗

PubMed1989

[The use of a computer for the diagnosis of comatose states in diabetics (a differential diagnostic algorithm)].

An algorithm for differential diagnosis of comatose conditions in patients with diabetes mellitus has been devised. The algorithm is intended for the general practitioner and non-specialized department. The algorithm uses the minimum of the crucial signs of comatose conditions, ensuring their diagnosis under the conditions of any hospital. The algorithm can be applied to the recognition of the typical variants of comatose conditions in a "pure" form. The amount of algorithm steps is minimized. The program of differential diagnosis is written in the Fokal language and realized on the computer "Elektronika BK 0010". The program is run in the dialogue mode. The algorithm is used in clinical practice and in the training process, with its efficacy being independent of the professional skills of the user.

Algorithms↗

PubMed1989

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↗

PubMed1994

[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↗

PubMed1996

[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↗