Big data and reference intervals

Yang, Dan; Su, Zihan; Zhao, Min

doi:10.1016/j.cca.2022.01.001

Cited by 12 publications

(5 citation statements)

References 71 publications

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“…In the field of medicine, the reference ranges of the normal values of various medical indicators are the normal fluctuation ranges of the corresponding indicators of the vast majority of normal people, and they are used to evaluate whether the measured corresponding indicators are normal and can provide a basis for disease diagnosis, health assessment, and disease treatment ( Horn and Pesce, 2003 ; Sun and Xu, 2014 ; Haeckel et al., 2021 ; Yang et al., 2022 ). There are many methods to determine the medical reference ranges ( Horn and Pesce, 2003 ; Sun and Xu, 2014 ; Haeckel et al., 2021 ; Yang et al., 2022 ). A medical reference range is usually determined by using normal distribution method or percentile method, mainly depending on whether the related data conform to a normal distribution ( Horn and Pesce, 2003 ; Sun and Xu, 2014 ; Haeckel et al., 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Two new methods for severity assessment of wheat stripe rust caused by Puccinia striiformis f. sp. tritici

Jiang

Wang

2022

Front. Plant Sci.

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Accurate severity assessment of wheat stripe rust caused by Puccinia striiformis f. sp. tritici is of great significance for phenotypic determination, prediction, and control of the disease. To achieve accurate severity assessment of the disease based on the actual percentages of lesion areas in the areas of the corresponding whole diseased leaves, two new methods were proposed for severity assessment of the disease. In the Adobe Photoshop 2022 software, the acquired images of single diseased leaves of each severity class of the disease were manually segmented, and the numbers of the leaf region pixels and lesion pixels of each diseased leaf were obtained by pixel statistics. After calculation of the actual percentages of lesion areas in the areas of the corresponding whole diseased leaves based on the obtained pixel numbers, the training sets and testing sets were constructed for each severity class by using the system sampling method with two sampling ratios of 4:1 and 3:2. Then the mean and standard deviation of the actual percentages of lesion areas contained in each training set were calculated, respectively. For each sampling ratio, two methods, one based on the midpoint value of the means of the actual percentages of lesion areas corresponding to two adjacent severity classes and the other based on the distribution range of most of the actual percentages of lesion areas, were used to determine the midpoint-of-two-adjacent-means-based actual percentage reference range and the 90%, 95%, and 99% reference ranges of the actual percentages of lesion areas for each severity class. According to the determined reference ranges, the severity of each diseased leaf in the training sets and testing sets was assessed. The results showed that high assessment accuracies (not lower than 85%) for the training sets and testing sets were achieved, demonstrating that the proposed methods could be used to conduct severity assessment of wheat stripe rust based on the actual percentages of lesion areas. This study provides a reference for accurate severity assessments of plant diseases.

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Section: Discussionmentioning

confidence: 99%

Two new methods for severity assessment of wheat stripe rust caused by Puccinia striiformis f. sp. tritici

Jiang

Wang

2022

Front. Plant Sci.

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“…e improved pbft algorithm uses the way of the master node out of the block, so there is no need for computing power competition, and the CPU utilization has been significantly reduced [20].…”

Section: Consensus Algorithmmentioning

confidence: 99%

Framework Design of Science and Technology Venture Capital Salary Management System Driven by Blockchain Technology

Yang

Niu²

2022

Mobile Information Systems

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The aim of this article is to study the framework design of science and technology venture capital salary management system driven by blockchain technology. Firstly, it expounds on the background and research significance of enterprise salary management. According to the current theory and research direction of salary management in domestic science and technology enterprises, combined with the mode of salary management in domestic enterprises, it analyzes the current situation and existing problems of enterprise salary management and the relevant algorithms driven by blockchain technology, among which the typical is consensus algorithm. Then, the salary management system is established, and the use cases of the system are analyzed according to the operation and business process of the system. Finally, according to the system requirements analysis, the overall network and software framework of the system are designed, the main business processes of the system are designed, and the database solution is put forward. The system test shows that the system finally completes the basic business of enterprise salary management, the operation interface is simple and convenient, the program runs stably, and can achieve the expected effect of demand analysis.

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“…Thus, we used data after normalization and outlier removal [4]. Bellview version 1.2.5 [14] was used to draw log difference plots to illustrate the relationship between log n+1 (bin count)log n (bin count) and the midpoint of the bins [5]. A straight line with a negative slope was constructed by identifying points by eye, and the x intercept and slope were used to calculate the mean and SD, respectively.…”

Section: Bhattacharya Methodsmentioning

confidence: 99%

“…The establishment of RIs using indirect methods roughly involves data acquisition, data cleaning, transformation of skewed data, elimination of outliers or error values, and selection of appropriate statistical methods to calculate the reference limits (RLs) [2,3]. Although indirect methods are obviously more concise in the implementation process compared to direct methods, the selection of an appropriate combination of data transformation, outlier removal, and indirect processes to establish RIs of laboratory analytes with different data distribution characteristics still raises controversies [5].…”

Section: Introductionmentioning

confidence: 99%

Effects of Using Different Indirect Techniques on the Calculation of Reference Intervals: Observational Study

Yang,

Su,

et al. 2023

J Med Internet Res

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Background Reference intervals (RIs) play an important role in clinical decision-making. However, due to the time, labor, and financial costs involved in establishing RIs using direct means, the use of indirect methods, based on big data previously obtained from clinical laboratories, is getting increasing attention. Different indirect techniques combined with different data transformation methods and outlier removal might cause differences in the calculation of RIs. However, there are few systematic evaluations of this. Objective This study used data derived from direct methods as reference standards and evaluated the accuracy of combinations of different data transformation, outlier removal, and indirect techniques in establishing complete blood count (CBC) RIs for large-scale data. Methods The CBC data of populations aged ≥18 years undergoing physical examination from January 2010 to December 2011 were retrieved from the First Affiliated Hospital of China Medical University in northern China. After exclusion of repeated individuals, we performed parametric, nonparametric, Hoffmann, Bhattacharya, and truncation points and Kolmogorov–Smirnov distance (kosmic) indirect methods, combined with log or BoxCox transformation, and Reed–Dixon, Tukey, and iterative mean (3SD) outlier removal methods in order to derive the RIs of 8 CBC parameters and compared the results with those directly and previously established. Furthermore, bias ratios (BRs) were calculated to assess which combination of indirect technique, data transformation pattern, and outlier removal method is preferrable. Results Raw data showed that the degrees of skewness of the white blood cell (WBC) count, platelet (PLT) count, mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and mean corpuscular volume (MCV) were much more obvious than those of other CBC parameters. After log or BoxCox transformation combined with Tukey or iterative mean (3SD) processing, the distribution types of these data were close to Gaussian distribution. Tukey-based outlier removal yielded the maximum number of outliers. The lower-limit bias of WBC (male), PLT (male), hemoglobin (HGB; male), MCH (male/female), and MCV (female) was greater than that of the corresponding upper limit for more than half of 30 indirect methods. Computational indirect choices of CBC parameters for males and females were inconsistent. The RIs of MCHC established by the direct method for females were narrow. For this, the kosmic method was markedly superior, which contrasted with the RI calculation of CBC parameters with high |BR| qualification rates for males. Among the top 10 methodologies for the WBC count, PLT count, HGB, MCV, and MCHC with a high-BR qualification rate among males, the Bhattacharya, Hoffmann, and parametric methods were superior to the other 2 indirect methods. Conclusions Compared to results derived by the direct method, outlier removal methods and indirect techniques markedly influence the final RIs, whereas data transformation has negligible effects, except for obviously skewed data. Specifically, the outlier removal efficiency of Tukey and iterative mean (3SD) methods is almost equivalent. Furthermore, the choice of indirect techniques depends more on the characteristics of the studied analyte itself. This study provides scientific evidence for clinical laboratories to use their previous data sets to establish RIs.

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Big data and reference intervals

Cited by 12 publications

References 71 publications

Two new methods for severity assessment of wheat stripe rust caused by Puccinia striiformis f. sp. tritici

Two new methods for severity assessment of wheat stripe rust caused by Puccinia striiformis f. sp. tritici

Framework Design of Science and Technology Venture Capital Salary Management System Driven by Blockchain Technology

Effects of Using Different Indirect Techniques on the Calculation of Reference Intervals: Observational Study

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