A new estimator to minimize the error due to breathing in the measurement of respiratory impedance.
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Humans↗
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Results for “Error minimization”
Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.
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Minimizing sample error in transmission electron microscopy.
The last few years have seen an increase in the use of electron microscopy, both for research and as a diagnostic tool in pathology. With the increase in the number of specimens being used for diagnostic purposes, limitations due to sampling error have become apparent. The method described is designed to help overcome this problem.
Microscopy, Electron↗
Minimizing binding errors using learned conjunctive features.
We have studied some of the design trade-offs governing visual representations based on spatially invariant conjunctive feature detectors, with an emphasis on the susceptibility of such systems to false-positive recognition errors-Malsburg's classical binding problem. We begin by deriving an analytical model that makes explicit how recognition performance is affected by the number of objects that must be distinguished, the number of features included in the representation, the complexity of individual objects, and the clutter load, that is, the amount of visual material in the field of view in which multiple objects must be simultaneously recognized, independent of pose, and without explicit segmentation. Using the domain of text to model object recognition in cluttered scenes, we show that with corrections for the nonuniform probability and nonindependence of text features, the analytical model achieves good fits to measured recognition rates in simulations involving a wide range of clutter loads, word size, and feature counts. We then introduce a greedy algorithm for feature learning, derived from the analytical model, which grows a representation by choosing those conjunctive features that are most likely to distinguish objects from the cluttered backgrounds in which they are embedded. We show that the representations produced by this algorithm are compact, decorrelated, and heavily weighted toward features of low conjunctive order. Our results provide a more quantitative basis for understanding when spatially invariant conjunctive features can support unambiguous perception in multiobject scenes, and lead to several insights regarding the properties of visual representations optimized for specific recognition tasks.
Artificial Intelligence↗
Minimizing binding errors using learned conjunctive features.
We have studied some of the design trade-offs governing visual representations based on spatially invariant conjunctive feature detectors, with an emphasis on the susceptibility of such systems to false-positive recognition errors-Malsburg's classical binding problem. We begin by deriving an analytical model that makes explicit how recognition performance is affected by the number of objects that must be distinguished, the number of features included in the representation, the complexity of individual objects, and the clutter load, that is, the amount of visual material in the field of view in which multiple objects must be simultaneously recognized, independent of pose, and without explicit segmentation. Using the domain of text to model object recognition in cluttered scenes, we show that with corrections for the nonuniform probability and nonindependence of text features, the analytical model achieves good fits to measured recognition rates in simulations involving a wide range of clutter loads, word size, and feature counts. We then introduce a greedy algorithm for feature learning, derived from the analytical model, which grows a representation by choosing those conjunctive features that are most likely to distinguish objects from the cluttered backgrounds in which they are embedded. We show that the representations produced by this algorithm are compact, decorrelated, and heavily weighted toward features of low conjunctive order. Our results provide a more quantitative basis for understanding when spatially invariant conjunctive features can support unambiguous perception in multiobject scenes, and lead to several insights regarding the properties of visual representations optimized for specific recognition tasks.
Algorithms↗
Combination forms save time, minimize documentation errors.
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Angina Pectoris↗
Minimizing medication errors: practical pointers for prescribers.
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Education, Medical, Undergraduate↗
Goniomegaly associated with a normal cornea, increased axial length, and minimal refractive error.
The association of a large axial length with a small refractive error and a normal corneal diameter should alert the lens implant surgeon to the possibility that goniomegaly is present. We report a patient whose intraoperative anterior chamber diameter was measured as 15 mm. It was necessary to insert a modified posterior chamber intraocular lens instead of an anterior chamber lens.
Anterior Chamber↗
Minimizing perspective error in gross photography.
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Photography↗
[Preoperative and peroperative tactics and techniques for minimizing peroperative errors and technical mistakes].
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Endocrine Surgical Procedures↗
Acoustic absorption measurement of human hair and skin within the audible frequency range.
Utilizing the two-microphone impedance tube method, the acoustic absorption of human skin and hair is measured in the frequency range 1-6 kHz. Various locations on a number of human subjects are measured to determine if the presence of bone or an air pocket affects the acoustic absorption of human skin. The absorption coefficient of human hair is also measured. Additional techniques are utilized to minimize errors due to sample mounting methods. Techniques are employed to minimize potential errors in sensor and sample locations. The results of these measurements are compared to relevant historical papers on similar investigations. Results for skin measurements compare well with previous work. Measured hair absorption data do not agree with previous work in the area but do coincide with expected trends, which previous works do not.
Absorption↗
3D real time methodology monitoring cement failures in THA.
The present work proposed a methodology to monitor cement microcrack formation in the cemented femoral stem construct using the acoustic emission technique. This technique provides a unique means to automatically tally the number of microcracks, to visualize microcrack distribution, and to animate the progress of crack formation in a given time window of a fatigue test. In this work, the formulation of microcrack source location was derived and a computer program was developed specifically for the proposed application. The program was validated using computer simulation and standard pencil lead break tests. It was found that the mathematical errors complied with the acceptable minimal error. Based on the pencil lead break tests, the average technical error used to estimate the resolution of this technique was 4.7 mm at the present stage. The program was then used to monitor the fatigue damage in precoated cemented femoral hip constructs loaded for a total of more than five million cycles. Two types of microcrack activities were observed in the experiments: Type I and Type II microcracks. A Type I microcrack was a crack that was captured by four or more sensors, and therefore its location was defined uniquely by a set of coordinates. A Type II microcrack was a crack that was captured by three or less sensors, therefore it was unlocatable. Both counts of Type I and Type II microcrack were tallied with respect to the day of fatigue tests. Acoustic emission microcrack graphs were used to visualize the distribution of Type I microcracks in the construct. It was found that the Type I microcracks distributed mainly over the proximal third of the stem. The amount of microcrack events decreased significantly as the number of loading cycles increased.
Adhesives↗
Patient safety in surgery: error detection and prevention.
Error in medicine is becoming a well recognized phenomenon. The U.S. Institute of Medicine's publication in 1999 included estimations that medical error is the eighth leading cause of death in the United States and results in up to 100,000 deaths annually. Retrospective studies and a few prospective studies are shedding more light on this challenging problem. Strategies to reduce error and increase patient safety have not been widely developed or embraced by surgeons for a variety of reasons. We provide a review on patient safety aimed at surgeons that includes definitions, incidence of errors including those in the surgical literature, causes of error, methods of error detection, and strategies to minimize errors and maximize patient safety.
Communication↗
On the optimality of the genetic code, with the consideration of coevolution theory by comparison of prominent cost measure matrices.
Statistical and biochemical studies have revealed non-random patterns in codon assignments. The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslation errors and point mutations, since it is known that when an amino acid is converted to another due to error, the biochemical properties of the resulted amino acid are usually very similar to those of the original one. In this study, using altered forms of the fitness functions used in the prior studies, we have optimized the parameters involved in the calculation of the error minimizing property of the genetic code so that the genetic code outscores the random codes as much as possible. This work also compares two prominent matrices, the Mutation Matrix and Point Accepted Mutations 74-100 (PAM(74-100)). It has been resulted that the hypothetical properties of the coevolution theory of the genetic code are already considered in PAM(74-100), giving more evidence on the existence of bias towards the genetic code in this matrix. Furthermore, our results indicate that PAM(74-100) is biased towards the single base mistranslation occurrences in second codon position as well as the frequency of amino acids. Thus PAM(74-100) is not a suitable substitution matrix for the studies conducted on the evolution of the genetic code.
Animals↗
Predicting forage indigestible NDF from lignin concentration.
We used chemical composition and in vitro digestibility data from temperate and tropical forages to develop relationships between indices of lignification and forage indigestible NDF. Neutral detergent fiber indigestibility increased nonlinearly as the lignin concentration of the NDF increased. Differences in estimated indigestible NDF using equations developed for a specific forage class (C3 and C4 grasses and legumes) were small and are probably not biologically significant when compared to those estimated from a common equation. Selected equations were compared with the Cornell Net Carbohydrate and Protein System (CNCPS) for the prediction of ADG. The linear equation (2.4 times NDF lignin content) used by the CNCPS and the Beef NRC had some of the largest errors due to mean bias. A log-log model [4.37 x (lignin/NDF)(.84)] provided the best combination of low total prediction error, low mean bias, and minimal error due to regression bias when permanganate lignin was used. A similar equation based on sulfuric acid lignin [6.17 x (lignin/NDF)(.77)] also met the above criteria. These equations then were evaluated with the CNCPS model against animal growth data from diets ranging in forage quality. Regardless of the equation used for predicting unavailable fiber, the CNCPS underpredicted daily gain, with mean biases ranging from -.10 to -.22 kg/d. Regression bias ranged from .13 to .14 kg/d and the coefficients differed from unity (P = .0001). The new equations gave numerically lower energy allowable ADG by steers compared to the linear equation currently used by the CNCPS model. The estimates were lower due to a higher predicted indigestible NDF, which resulted in a lower estimated forage energy value.
Animal Feed↗
Correction approaches for doubly labeled water in situations of changing background water abundance.
Doubly labeled water (DLW) is an accurate, portable method for measuring free-living energy expenditure. However, under certain conditions shifts in baseline abundance of deuterium and oxygen-18 tracers used in the method may produce errors in derivation of both turnover (k) rates and calculated energy expenditure. Present objectives were to examine during what experimental situations baseline errors arise and to address means of correcting for such baseline shifts so that consequent errors in energy expenditure calculations are minimized. Under conditions where shifts in baseline abundance for deuterium and oxygen-18 parallel abundances corresponding to the natural meteoric water ratio, self-compensating changes in k values for both deuterium and oxygen will result in minimal error to the DLW energy expenditure calculations, provided that the dose ratio of isotopes also mimics the meteoric water line. However, in situations where relative shifts in abundance of each isotope across the measurement period are not in parallel relative to the natural meteoric water line, then the potential for larger DLW errors exists. Optimally, subjects should equilibrate with the new water source. Failing this, correction for shifting baseline can be accomplished by measuring isotopic abundance changes in a control group of subjects not given the DLW dose, but performing similar tasks and consuming the same diet as the group given DLW. Alternatively, theoretically based correction values can be calculated given knowledge of the abundances of the final drinking water and the interval time that subjects consumed the new fluid.
Body Water↗
Trauma registry data validation: Essential for quality trauma care.
BACKGROUND: The main function of a trauma registry is to assess quality assurance and performance improvement (QA/PI) in an individual institution. Nonvalidated registry data may produce unreliable reports and QA/PI information. This study examines the types of data entry errors in a trauma registry database; the effect of errors on time variable estimates, case ascertainment and statistical measurement; dynamics of error occurrence; and data validation (DV) scheme for a trauma registry. METHODS: Query and cross-tabulation techniques were used to expose a variety of data entry errors. Conceptual aspect for each type of error in DV, especially with respect to QA/PI, is given. RESULTS: Findings of different errors are provided: out-of-range time values; false positive and false negative errors; errors of commission and omission; duplication errors; errors in demographics; and errors because of inconsistent and incongruent coding. Error rates were less than 3% in commonly occurring data, such as scene time, demographics, hospital discharge and transportation, and greater in less commonly occurring but important data, such as thoracic aorta injury (9.5%) and audit filter for admit Glasgow Coma Scale in emergency department (55.6%). Dynamics of error occurrence that can prevent or minimize errors is described. The main features of a data validation scheme are displayed. CONCLUSIONS: Errors in a trauma registry database cause invalid frequencies, rates, time estimates and statistical measures and affect QA/PI in trauma care. Every functioning trauma registry should develop an on-going program for DV.
Bias↗
Application of the keyhole technique to T1rho relaxation mapping.
PURPOSE: To demonstrate the feasibility of using the keyhole technique to minimize error in a least squares regression estimation of T(1rho) from magnetic resonance (MR) image data. MATERIALS AND METHODS: The keyhole method of partial k-space acquisition was simulated using data from a virtual phantom and MR images of ex vivo bovine and in vivo human cartilage. T(1rho) maps were reconstructed from partial k-space (keyhole) image data using linear regression, and error was measured with relation to T(1rho) maps created from the full k-space images. An error model was created based on statistical theory and fitted to the error measurements. RESULTS: T(1rho) maps created from keyhole images of a human knee produced levels of error on the order of 1% while reducing standard image acquisition time approximately by half. The resultant errors were strongly correlated with expectations derived from statistical theory. CONCLUSION: The error model can be used to analytically optimize the keyhole method in order to minimize the overall error in the estimation of the relaxation parameter of interest. The keyhole method can be generalized to significantly expedite all forms of relaxation mapping.
Animals↗