scholarly journals New Bayesian method for multiextremal optimization

2020 ◽  
Vol 7 (0) ◽  
Author(s):  
Natalija Pozniak ◽  
Leonidas Sakalauskas
Keyword(s):  
Bayesian Method ◽  
Multiextremal Optimization

BAYESIAN METHOD FOR RAPID MULTI-WELL INTERPRETATION OF WELL LOGS AND CORE DATA IN UNCONVENTIONAL FORMATIONS

2020 ◽  
Author(s):  
Tianqi Deng ◽  
◽  
Joaquín Ambía ◽  
Carlos Torres-Verdín ◽  
◽  
...  
Keyword(s):  
Bayesian Method ◽  
Well Logs ◽  
Core Data

scholarly journals Age-specific cut-off levels of anti-Müllerian hormone can be used as diagnostic markers for polycystic ovary syndrome

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Fahimeh Ramezani Tehrani ◽  
Maryam Rahmati ◽  
Fatemeh Mahboobifard ◽  
Faezeh Firouzi ◽  
Nazanin Hashemi ◽  
...  
Keyword(s):  
Bayesian Method ◽  
Polycystic Ovary ◽  
Characteristic Curve ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Control Group ◽  
Age Group ◽  
Predictive Values ◽  
Pcos Group

Abstract Background The majority of available studies on the AMH thresholds were not age-specific and performed the receiver operating characteristic curve (ROC) analysis, based on variations in sensitivity and specificity rather than positive and negative predictive values (PPV and NPV, respectively), which are more clinically applicable. Moreover, all of these studies used a pre-specified age categorization to report the age-specific cut-off values of AMH. Methods A total of 803 women, including 303 PCOS patients and 500 eumenorrheic non-hirsute control women, were enrolled in the present study. The PCOS group included PCOS women, aged 20–40 years, who were referred to the Reproductive Endocrinology Research Center, Tehran, Iran. The Rotterdam consensus criteria were used for diagnosis of PCOS. The control group was selected among women, aged 20–40 years, who participated in Tehran Lipid and Glucose cohort Study (TLGS). Generalized additive models (GAMs) were used to identify the optimal cut-off points for various age categories. The cut-off levels of AMH in different age categories were estimated, using the Bayesian method. Main results and the role of chance Two optimal cut-off levels of AMH (ng/ml) were identified at the age of 27 and 35 years, based on GAMs. The cut-off levels for the prediction of PCOS in the age categories of 20–27, 27–35, and 35–40 years were 5.7 (95 % CI: 5.48–6.19), 4.55 (95 % CI: 4.52–4.64), and 3.72 (95 % CI: 3.55–3.80), respectively. Based on the Bayesian method, the PPV and NPV of these cut-off levels were as follows: PPV = 0.98 (95 % CI: 0.96–0.99) and NPV = 0.40 (95 % CI: 0.30–0.51) for the age group of 20–27 years; PPV = 0.96 (95 % CI: 0.91–0.99) and NPV = 0.82 (95 % CI: 0.78–0.86) for the age group of 27–35 years; and PPV = 0.86 (95 % CI: 0.80–0.94) and NPV = 0.96 (95 % CI: 0.93–0.98) for the age group of 35–40 years. Conclusions Application of age-specific cut-off levels of AMH, according to the GAMs and Bayesian method, could elegantly assess the value of AMH in discriminating PCOS patients in all age categories.

scholarly journals A Novel Multi-Mode Bayesian Method for the Process Monitoring and Fault Diagnosis of Coal Mills

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 22914-22926
Author(s):  
Wei Fan ◽  
Shaojun Ren ◽  
Qinqin Zhu ◽  
Zhijun Jia ◽  
Delong Bai ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Process Monitoring ◽  
Bayesian Method ◽  
Multi Mode

Usefulness of seroconversion rates for comparing infection pressures between countries

2010 ◽  
Vol 139 (4) ◽  
pp. 636-643 ◽  
Author(s):  
J. SIMONSEN ◽  
P. TEUNIS ◽  
W. VAN PELT ◽  
Y. VAN DUYNHOVEN ◽  
K. A. KROGFELT ◽  
...  
Keyword(s):  
Bayesian Method ◽  
Healthy Population ◽  
Surveillance Systems ◽  
National Surveillance ◽  
Serum Samples ◽  
Cross Sectional ◽  
Infection Pressure ◽  
Control Programmes ◽  
True Infection ◽  
Rate Ratios

SUMMARYSalmonella is a frequent cause of foodborne illness. However, since most symptomatic cases are not diagnosed, the true infection pressure is unknown. Furthermore, national surveillance systems have different sensitivities that limit inter-country comparisons. We have used recently developed methods for translating measurements of Salmonella antibodies into estimates of seroincidence: the frequency of infections including asymptomatic cases. This methodology was applied to cross-sectional collections of serum samples obtained from the general healthy population in three European countries. Denmark and The Netherlands had the lowest seroincidence (84169 infections/1000 person-years), whereas Poland had the highest seroincidence (547/1000 person-years). A Bayesian method for obtaining incidence rate ratios was developed; this showed a 6·3 (95% credibility interval 3·3–12·5) higher incidence in Poland than in Denmark which demonstrates that this methodology has a wider applicability for studies of surveillance systems and evaluation of control programmes.

scholarly journals Classification of SSVEP-based BCIs using Genetic Algorithm

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hamideh Soltani ◽  
Zahra Einalou ◽  
Mehrdad Dadgostar ◽  
Keivan Maghooli
Keyword(s):  
Genetic Algorithm ◽  
Dimension Reduction ◽  
Classification Accuracy ◽  
Bayesian Method ◽  
Computer Interface ◽  
Support Vector ◽  
Svm Classifier ◽  
Effective Dimension ◽  
Effective Dimension Reduction

AbstractBrain computer interface (BCI) systems have been regarded as a new way of communication for humans. In this research, common methods such as wavelet transform are applied in order to extract features. However, genetic algorithm (GA), as an evolutionary method, is used to select features. Finally, classification was done using the two approaches support vector machine (SVM) and Bayesian method. Five features were selected and the accuracy of Bayesian classification was measured to be 80% with dimension reduction. Ultimately, the classification accuracy reached 90.4% using SVM classifier. The results of the study indicate a better feature selection and the effective dimension reduction of these features, as well as a higher percentage of classification accuracy in comparison with other studies.

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