METHOD FOR MODELING NORMATIVE SONOGRAPHIC PARAMETERS OF THYROID IN BOYS WITH DIFFERENT CONSTITUTIONAL TYPES

• 1. 一种基于Rocchio算法的甲状腺超声特征肿瘤分级系统 [P] . 中国专利： CN113887228A . 2022-01-04
• 2. 对不同来源的业务数据进行规范化处理的方法及系统 [P] . 中国专利： CN103309907B . 2017.02.01
• 3. METHOD FOR MODELING NORMATIVE SONOGRAPHIC PARAMETERS OF THYROID IN GIRLS WITH DIFFERENT CONSTITUTIONAL TYPES [P] . UA44871U . 2009-10-12

  机译： 不同本构型女孩中甲状腺规范超声参数的建模方法

• 4. method for modelling of normative parameters of the central hemodynamycs IN adolescent boys with various somatotypes depending on constitutional features [P] . UA47413U . 2010-01-25

  机译： 体格特征的青少年体型中枢血流动力学规范参数建模的方法

• 5. METHOD FOR MODELING NORMATIVE RHEOGRAPHIC PARAMETERS OF CENTRAL HEMODYNAMICS IN YOUNG MEN OF VARIOUS CONSTITUTIONAL TYPES [P] . UA42710U . 2009-07-10

  机译： 各种构型青年男子中央血流动力学规范流变学参数的建模方法

• 1. Pathology Verified Concomitant Papillary Thyroid Carcinoma in the Sonographically Suspected Thyroid Lymphoma：A Case Report [J] . Qiong Wu, Bo Zhang, Yu-xin Jiang, 中国医学科学杂志（英文版） . 2016,第001期
• 2. Parameter Optimization of Interval Type-2 Fuzzy Neural Networks Based on PSO and BBBC Methods [J] . Jiajun Wang, Tufan Kumbasar 自动化学报（英文版） . 2019,第001期
• 3. Parameter Optimization of Interval Type-2 Fuzzy Neural Networks Based on PSO and BBBC Methods [J] . Jiajun Wang, Tufan Kumbasar 自动化学报：英文版 . 2019,第001期
• 4. A predictive model of thyroid malignancy using clinical, biochemical and sonographic parameters for patients in a multi-center setting [J] . Jia Liu, Dongmei Zheng, Qiang Li, BMC Endocrine Disorders . 2018,第1期
• 5. Comparison of Diverse Methods of Identifying the Parameters of Various Models of Solar Cells for Three Technologies Types [J] . B. Bouachrine, M. Kourchi, M. Ajaamoum, International review of electrical engineering . 2014,第6期
• 6. Robust Wald-type methods for testing equality between two populations regression parameters: A comparative study under the logistic model [J] . Bianco Ana M., Boente Graciela, Rodrigues Isabel M. Computational statistics & data analysis . 2020,第1期
• 7. A Local Sensitivity Analysis Method for Developing Biological Models with Identifiable Parameters: Application to L-type Calcium Channel Modelling [C] . Sher Anna, Wang Ken, Wathen Andrew, 2010 Sixth IEEE International Conference on e-Science . 2010
• 8. Improved Methods for Statistical Inference in the Context of Various Types of Parameter Variation [D] . Casini, Alessandro. 2019
• 9. A predictive model of thyroid malignancy using clinical biochemical and sonographic parameters for patients in a multi-center setting [O] . Jia Liu, Dongmei Zheng, Qiang Li, 2018
• 10. Регресійні моделі нормативних сонографічних параметрів щитоподібної залози в залежності від особливостей будови тіла у чоловіків і жінок різного віку = Regression models normative sonographic parameters thyroid gland depending on the characteristics of the body structure in men and women of all ages [O] . Gunas I. V., Vastyanov R. S., Majewski O. Ye., 2015

• 1. Application of SVR Models in Stock Index Forecast Based on Different Parameter Search Methods [J] . Jiechao Chen ,Huazhou Chen ,Yajuan Huo . 统计学期刊（英文） . 2017,第2期
• 2. Approximate Solution of Lane-Emden Type Equations Using Variation of Parameters Method with an Auxiliary Parameter [J] . Asmaa S. Khalifa ,Hany N. Hassan . 应用数学与应用物理（英文） . 2019,第4期
• 3. 甲状腺乳头状癌不同组织学亚型BRAF突变与超声特征的相关性研究 [C] . 窦蕊 ,钱林学 . 2018海峡两岸医药卫生交流与合作会议暨第十届海峡两岸超声医学高端论坛 . 2018
• 4. 应用Logistic回归分析方法研究甲状腺良恶性结节的超声特征 [A] . 张敏 . 2014