Prediction of spherical equivalent refraction and axial length in children based on machine learning

Purpose: Recently, the proportion of patients with high myopia has shown a continuous growing trend, more toward the younger age groups. This study aimed to predict the changes in spherical equivalent refraction (SER) and axial length (AL) in children using machine learning methods. Methods: This study is a retrospective study. The cooperative ophthalmology hospital of this study collected data on 179 sets of childhood myopia examinations. The data collected included AL and SER from grades 1 to 6. This study used the six machine learning models to predict AL and SER based on the data. Six evaluation indicators were used to evaluate the prediction results of the models. Results: For predicting SER in grade 6, grade 5, grade 4, grade 3, and grade 2, the best results were obtained through the multilayer perceptron (MLP) algorithm, MLP algorithm, orthogonal matching pursuit (OMP) algorithm, OMP algorithm, and OMP algorithm, respectively. The R2 of the five models were 0.8997, 0.7839, 0.7177, 0.5118, and 0.1758, respectively. For predicting AL in grade 6, grade 5, grade 4, grade 3, and grade 2, the best results were obtained through the Extra Tree (ET) algorithm, MLP algorithm, kernel ridge (KR) algorithm, KR algorithm, and MLP algorithm, respectively. The R2 of the five models were 0.7546, 0.5456, 0.8755, 0.9072, and 0.8534, respectively. Conclusion: Therefore, in predicting SER, the OMP model performed better than the other models in most experiments. In predicting AL, the KR and MLP models were better than the other models in most experiments.

Econometric ridge regression models of risk-sensitive sunflower yield / Modelos economométricos de regressão de rendimento de girassol sensível ao risco

The article considers econometric ridge regression models of the risk-sensitive sunflower yield on the example of an export-oriented agricultural crop. In particular, we have proved that despite the functional mulcollinearity of the predictors in the sunflower yield model with respect to risk caused by the algorithm peculiarities of the hierarchy analysis methods, the ridge regression procedure makes it possible to obtain its complete specification and provide biased but stable estimates of the forecast parameters in the case of uncertain input variables. It has been substantiated that the rational value of the displacement parameters is expedient to be established using a graphical interpretation of the ridge wake as the border of fast and slow fluctuations in the estimates of the ridge regression coefficients. Econometric models were calculated using SPSS Statistics, Mathcad and FAR-AREA 4.0 software. The empirical basis for forecast calculations was the assessment of trends in sunflower production in all categories of farms in the Rostov region of Russia for the period of 2008-2018. The calculation results of econometric models made it possible to develop three author's scenarios for the sunflower production in the region, namely, inertial, moderate, and optimistic ones that consider the export-oriented strategy of the agro-industrial complex.(AU)

O artigo considera modelos econométricos de regressão de rendimento de girassol sensível ao risco sobre o exemplo de uma cultura agrícola orientada para a exportação. Em particular, provamos que apesar da multicolinearidade funcional dos preditores no modelo de rendimento de girassol com relação ao risco causado pelas peculiaridades dos algoritmos dos métodos de análise hierárquica, o procedimento de regressão de cristas permite obter sua especificação completa e fornecer estimativas tendenciosas, mas estáveis dos parâmetros de previsão no caso de variáveis de entrada incertas. Foi comprovado que o valor racional dos parâmetros de deslocamento é conveniente de ser estabelecido usando uma interpretação gráfica da esteira da crista como fronteira das flutuações rápidas e lentas nas estimativas dos coeficientes de regressão da crista. Os modelos econométricos foram calculados usando o software SPSS Statistics, Mathcad e FAR-AREA 4.0. A base empírica para os cálculos de previsão foi a avaliação das tendências da produção de girassol em todas as categorias de fazendas na região de Rostov na Rússia para o período de 2008-2018. Os resultados dos cálculos dos modelos econométricos permitiram desenvolver três cenários de autor para a produção de girassol na região, a saber, os cenários inercial, moderado e otimista que consideram a estratégia orientada à exportação do complexo agroindustrial.(AU)

HisCoM-GGI: Software for Hierarchical Structural Component Analysis of Gene-Gene Interactions

Gene-gene interaction (GGI) analysis is known to play an important role in explaining missing heritability. Many previous studies have already proposed software to analyze GGI, but most methods focus on a binary phenotype in a case-control design. In this study, we developed “Hierarchical structural CoMponent analysis of Gene-Gene Interactions” (HisCoM-GGI) software for GGI analysis with a continuous phenotype. The HisCoM-GGI method considers hierarchical structural relationships between genes and single nucleotide polymorphisms (SNPs), enabling both gene-level and SNP-level interaction analysis in a single model. Furthermore, this software accepts various types of genomic data and supports data management and multithreading to improve the efficiency of genome-wide association study data analysis. We expect that HisCoM-GGI software will provide advanced accessibility to researchers in genetic interaction studies and a more effective way to understand biological mechanisms of complex diseases.

Relationship between geographic environment and blood urea nitrogen reference values of healthy people / 吉林大学学报(医学版)

Objective:To discuss the relationship between the geographic environment and blood urea nitrogen(BUN) reference values of the healthy people,and to explore the distributional rule of BUN reference values of the healthy people,and to provide the scientific foundation for establishing the BUN reference value standards of different areas.Methods:A total of 23 geographic factors and 33 521 BUN reference values of healthy adults measured by 403 medical facilities from 23 provinces,4 municipalities and 5 autonomous regions were collected.The spatial autocorrelation analysis was used to determine the spatial autocorrelation of the sample data;the correlation analysis was used to detect the factors which correlated significantly with the BUN reference values;the multiple linear regression,principle component analysis and ridge regression analysis were respectively used to construct the predicted models;the paired-sample t test was used to choose the optimal model;the distribution map of BUN reference values was built by geostatistic analysis.Results:There were 5 geographic factors,latitude(X2),altitude(X3),annual mean temperature(X5),annual mean relative humidity(X6) and annual precipitation(X7),correlated significantly with the BUN reference values.The regression equation of optimal model was Y

Spatial Variation of Reference Value of Tumor Biomarker : Alpha-L-Fucosidase / 中山大学学报(医学科学版)

[Objective] To refer a geographical distribution rule of alpha-L-fucosidase (AFU) reference values for the health adults in China via exploring its spatial distribution trend and its correlation with geographical factors.[Methods] A total of 6564 samples of AFU reference values from 66 administrative units in the years 2004-2015 were collected,male and female of which were 3701 cases (56.4％) and 2863 cases (46.3％).A research concerning AFU reference values in whole country were calculated using methods of information content and ridge regression.[Results] AFU reference values for Chinese healthy adults were influenced by geographical factors and presented autocorrelation,and it showed eastern and northern areas were highery than western and southern areas.[Conclusions] AFU reference values have a spatial variation and the regional disparities should be considered in practice.