Advanced Joint Bayesian Method for Face Verification

2015 ◽  
Vol 10 (2) ◽  
pp. 346-354 ◽  
Author(s):  
Yicong Liang ◽  
Xiaoqing Ding ◽  
Jing-Hao Xue
Keyword(s):  
Bayesian Method ◽  
Face Verification

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

CROSS-AGE FACE VERIFICATION USING FACE AGING

2020 ◽  
Author(s):  
Alankrit Khanna ◽  
Anisha Thakur ◽  
Aprajita Tewari ◽  
Aruna Bhat
Keyword(s):  
Face Verification ◽  
Face Aging
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