Background: Vancomycin is commonly dosed using standard weight-based methods before dose adjustments are made through therapeutic drug monitoring (TDM). However, variability in initial dosing can lead to suboptimal th...
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Background: Vancomycin is commonly dosed using standard weight-based methods before dose adjustments are made through therapeutic drug monitoring (TDM). However, variability in initial dosing can lead to suboptimal therapeutic outcomes. A predictive model that personalizes initial dosing based on patient-specific pharmacokinetic factors prior to administration may enhance target attainment and minimize the need for subsequent dose adjustments. Objective: This study aimed to develop and evaluate a machine learning (ML)-based algorithm to predict whether an initial vancomycin dose falls within the therapeutic range of the 24-hour area under the curve to minimum inhibitory concentration, thereby optimizing the initial vancomycin dosage. Methods: A retrospective cohort study was conducted using hospitalized patients who received intravenous vancomycin and underwent pharmacokinetic TDM consultation (n=415). The cohort was randomly divided into training and testing datasets in 7:3 ratio, and multiple ML techniques were used to develop an algorithm for optimizing initial vancomycin dosing. The optimal algorithm, referred to as the OPTIVAN algorithm, was selected and validated using an external cohort (n=268). We evaluated the performance of 4 ML models: gradient boosting machine, random forest (RF), support vector machine (SVM), and eXtreme gradient boosting (XGB). Additionally, a web-based clinical support tool was developed to facilitate real-time vancomycin TDM application in clinical practice. Results: The SVM algorithm demonstrated the best predictive performance, achieving an area under the receiver operating characteristic curve (AUROC) of 0.832 (95% CI 0.753-0.900) for the training dataset and 0.720 (95% CI 0.654-0.783) for the external validation dataset. The gradient boosting machine followed closely with AUROC scores of 0.802 (95% CI 0.667-0.857) for the training dataset and 0.689 (95% CI 0.596-0.733) for the validation dataset. In contrast, both XGB and RF exhi
Rectourethral fistula (RUF) is associated with poor quality of life related to urinary functional symptoms (pneumaturia, fecaluria, urine passing through the rectum) or urinary tract infections (upper or lower, often ...
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The Auditory Brainstem Response (ABR) is an essential diagnostic indicator of overall health of cochlea, auditory brainstem and midbrain, used extensively in both basic research and clinical studies. A key quantificat...
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The Auditory Brainstem Response (ABR) is an essential diagnostic indicator of overall health of cochlea, auditory brainstem and midbrain, used extensively in both basic research and clinical studies. A key quantification of the ABR is threshold, the lowest sound level that elicits a response. Because the morphology of ABR waveforms shift with stimulus level and the overall signal-to-noise ratio is low, threshold estimation is not straightforward. Although several algorithmic approaches have been proposed, the current standard practice remains the visual evaluation of ABR waveforms as a function of stimulus level. We developed an algorithm based on the cross-correlation of two independent averages of responses to the same stimulus. For each stimulus level, the individual responses to each tone-pip are randomly split into two groups. The median waveform for each group is calculated, and then the normalized cross-correlation between these median waveforms is obtained. This process is repeated 500 times to obtain a resampled cross-correlation distribution. For each frequency, the mean values of these distributions are computed for each level and fit with a sigmoid or a power law function to estimate the threshold. algorithmic thresholds demonstrated robust and accurate performance, achieving 92% accuracy within +/- 10 dB of human-rated thresholds on a large pool of mouse data. This performance was better than that of several published algorithms on the same dataset. This algorithm has now fully replaced the manual estimation of ABR thresholds for our preclinical studies, thereby saving significant time and enhancing objectivity in the process.
In order to maximize humanoid robot navigation, this paper introduces the Enhanced DAYANI Arc Contour Intelligent (EDACI) Method, which integrates Dynamic Window Approach (DWA) to choose the best walking parameters fo...
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In order to maximize humanoid robot navigation, this paper introduces the Enhanced DAYANI Arc Contour Intelligent (EDACI) Method, which integrates Dynamic Window Approach (DWA) to choose the best walking parameters for avoiding obstacles and smooth trajectory management. EDACI algorithm provides the best response to guide humanoid robots to the goal by avoiding obstacles and preparing a smooth trajectory. Further, DWA optimizes the walking pattern of humanoid robots by controlling their velocity while encountering an obstacle and finding a smooth trajectory. The performance of the proposed controller is examined by implementing it in humanoid NAOs for navigation in several simulated and experimental terrains. It is implemented on a single humanoid robot for navigation in static and dynamic environments and on multiple humanoid robots on a single platform. Navigation of multiple robots has to deal with the situation of conflict where one robot behaves as a dynamic obstacle to the other. It is solved by setting a Dining Philosopher Controller (DPC) in the base technique. The results obtained from the simulations and experiments have a divergence below 5 %, which demonstrates a satisfactory relation between them. The proposed controller's efficacy is demonstrated by comparing the torque developed at different joints with contrast to the inbuilt controller of NAO. The results show good improvement in torque produced at all joints. In addition, it is compared with an existing controller for navigation, which displays superiority of the proposed controller.
Confocal Raman microscopy is important for characterizing 2 D materials, but its low throughput significantly hinders its applications. For metastable materials such as graphene oxide(GO), the low throughput is aggrav...
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Confocal Raman microscopy is important for characterizing 2 D materials, but its low throughput significantly hinders its applications. For metastable materials such as graphene oxide(GO), the low throughput is aggravated by the requirement of extremely low laser dose to avoid sample damage. Here we introduce algorithm-improved confocal Raman microscopy(ai-CRM), which increases the Raman scanning rate by one to two orders of magnitude with respect to state-of-the-art works for a variety of 2 D materials. Meanwhile, GO can be imaged at a laser dose that is two to three orders of magnitude lower than previously reported, such that laser-induced variations of the material properties can be avoided. ai-CRM also enables fast and spatially resolved quantitative analysis, and is readily extended to 3 D mapping of composite materials. Since ai-CRM is based on general mathematical principles, it is cost-effective, facile to implement and universally applicable to other hyperspectral imaging methods.
Intersection computation of convex sets is a typical problem in distributed *** this paper,the algorithm implementation is investigated for distributed convex intersection computation *** a multi-agent network,each ag...
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Intersection computation of convex sets is a typical problem in distributed *** this paper,the algorithm implementation is investigated for distributed convex intersection computation *** a multi-agent network,each agent is associated with a convex *** objective is for all the agents to achieve an agreement within the intersection of the associated convex sets.A distributed"projected consensus algorithm"is employed,and the computation of the projection term is converted to a constrained optimization *** solution of the optimization problem is determined by Karush-Kuhn-Tucker(KKT)*** implementable algorithms based on the simplex method are introduced to solve the optimization *** numerical examples are given to illustrate the effectiveness of the algorithms.
An algorithm for medical diagnosis assistance is described. In this algorithm, the patient is identified following the simultaneous evaluation of its degree of similarity with a given disease, as well as the extent of...
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An algorithm for medical diagnosis assistance is described. In this algorithm, the patient is identified following the simultaneous evaluation of its degree of similarity with a given disease, as well as the extent of disagreement with the rest of diseases considered in the differential diagnosis. In an example the algorithm is applied to the diagnosis assistance of some neuropathies.
This letter presents a Rubik metamaterial with sextuple orbital angular momentum (OAM) capabilities. The design is based on a comprehensive algorithm that draws inspiration from the Rubik's cube. This metamaterial...
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This letter presents a Rubik metamaterial with sextuple orbital angular momentum (OAM) capabilities. The design is based on a comprehensive algorithm that draws inspiration from the Rubik's cube. This metamaterial can generate multiple phased vortex waves using only one model and is easily constructed from metallic blocks with varying heights. The performance of the metamaterial is verified at 18 GHz with a gain of over 30 dB. A faster verification process is achieved using an automated program based on macroscript for height-adjusted Rubik metamaterials, which is more efficient than manual operations. By calculating the purity of the sextuple OAMs, it can be determined that the Rubik model is capable of generating multiple phased vortex wave beams as effectively as possible. This Rubik metamaterial has potential applications in experimental and educational settings, particularly with the growing trend in three-dimensional printing.
Springback is the most common defect in sheet metal forming, especially for the advanced high-strength steel (AHSS) parts. The compensation method is an effective way to overcome this defect by modifying the die-face....
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Springback is the most common defect in sheet metal forming, especially for the advanced high-strength steel (AHSS) parts. The compensation method is an effective way to overcome this defect by modifying the die-face. A new geometrical springback compensation algorithm based on the advanced displacement adjustment (DA) method is proposed in this paper for automobile AHSS parts. The die-face is reconstructed by the non-uniform rational B-spline surface with the advantage of UV curves;furthermore, the continuity and topology of the die-face are also studied. The high-quality geometry compensation die-face obtained from this algorithm can be directly applied to actual machining. To reduce the time and cost of the die manufacturing, this algorithm is seamlessly integrated into the CATIA platform. A new compensation user-defined feature is created, which can meet the need for iterative compensation and parametric association. At the end of this paper, two engineering examples of AHSS parts verify the feasibility and validity of this algorithm and system.
作者：
Zhao, CDWenzhou Univ
Dept Math & Informat Sci Zhejiang 325035 Peoples R China
The present paper discusses the algorithm and mechanization to the Cauchy problem of parabolic equation. The author uses the initial data to construct the solutions that satisfy the initial condition and obtain a brie...
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The present paper discusses the algorithm and mechanization to the Cauchy problem of parabolic equation. The author uses the initial data to construct the solutions that satisfy the initial condition and obtain a brief algorithm to this problem. Thereafter, the algorithm is used in Map/e to solve this Cauchy problem automatically. (c) 2004 Elsevier Inc. All rights reserved.
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