new updates 01/09

_pages/about.md

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 I am Khanh, a Lecturer at [Department of Probability and Statistics](https://sites.google.com/hcmus.edu.vn/math-xstk/), [Faculty of Mathematics and Computer Science,](https://math.hcmus.edu.vn/en/) University of Science, Vietnam National University Ho Chi Minh city. 
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-I received my Bachelor's degree in Oct 2012, after finishing four years of honors program at the Faculty of Mathematics and Computer Science, University of Science, Vietnam National University, Ho Chi Minh city. I graduated top of my class and I did research on mathematical analysis and statistics. After graduating, I was offered a teaching assistant position at the Faculty of Mathematics and Computer Science. During this period, I was fascinated by applications of Statistics in life science. This had motivated me to become a researcher in applied statistics. In 2014, I was selected as a Ph.D. student in Statistics at [Department of Statistical Sciences](https://www.stat.unipd.it/en/) with the first rank in the ranking table of CARIPARO Ph.D. scholarship at the [University of Padova](https://www.unipd.it/), Italy. During three years of my Ph.D. program, I was working hard on the subject ``Statistical evaluation of diagnostic tests under verification bias'' which is an interested topic in Medical Statistics. I defended my doctoral dissertation in March 2017, and received great appreciation from the committee. The full text of my Ph.D thesis can be found [here](https://hdl.handle.net/11577/3425717). In addition, I successful developed an R package (named bcROCsurface) and a web interface to support researchers in the evaluation of predictive ability of diagnostic tests. For these results, I was awarded the Prize for Research 2017 of Department of Statistical Sciences, University of Padova.
+I received my Bachelor's degree in Oct 2012, after finishing four years of honors program at the Faculty of Mathematics and Computer Science, University of Science, Vietnam National University, Ho Chi Minh city. I graduated top of my class and I did research on mathematical analysis and statistics. After graduating, I was offered a teaching assistant position at the Faculty of Mathematics and Computer Science. During this period, I was fascinated by applications of Statistics in life science. This had motivated me to become a researcher in applied statistics. In 2014, I was selected as a Ph.D. student in Statistics at [Department of Statistical Sciences](https://www.stat.unipd.it/en/) with the first rank in the ranking table of CARIPARO Ph.D. scholarship at the [University of Padova](https://www.unipd.it/), Italy. During three years of my Ph.D. program, I was working hard on the subject "Statistical evaluation of diagnostic tests under verification bias" which is an interested topic in Medical Statistics. I defended my doctoral dissertation in March 2017, and received great appreciation from the committee. The full text of my Ph.D thesis can be found [here](https://hdl.handle.net/11577/3425717). In addition, I successful developed an R package (named bcROCsurface) and a web interface to support researchers in the evaluation of predictive ability of diagnostic tests. For these results, I was awarded the Prize for Research 2017 of Department of Statistical Sciences, University of Padova.
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 From May 2017 to June 2022, I was a postdoctoral research fellow at the department and studied on the several research projects with regard to te problem of evaluating the accuracy of diagnostic test (or biomarker, or classifier in general) and meta-analysis. The details of all projects can be found in [my CV](/cv/) page. Working on these projects, I gained valuable experience in data analysis for biomedical data and gene expression data, especially for incurable diseases, such as epithelial ovarian cancer, Alzheimer's disease, type 2 diabetes mellitus, breast cancer. I have accumulated valuable experiences on modeling the model for missing data mechanism and on mixed-effect models, moreover I improved my coding skill in R and C/C++ programming. Last but not least, I understood the important role of diagnostic tests or screening tests (or biomarkers) for early detecting serious diseases, e.g., ovarian cancer, breast cancer and diabetes. These trigger my further research activities in biomedical statistics with regard to evaluating diagnostic tests (screening tests) and cancer research. 
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_pages/cv.md

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 # Education
 
-* B.S. in Mathematics and Computer Sciences, Faculty of Mathematics and Computer Science, University of Science, Vietnam National University - Ho Chi Minh city, Vietnam, 2012
-* Ph.D in Statistical Sciences, Department of Statistical Sciences, University of Padova, 2017
+* 1st January 2014 - 31th December 2016. Ph.D in Statistical Sciences, Department of Statistical Sciences, University of Padova.<br>Thesis title: *Statistical evaluation of diagnostic tests under verification bias*.<br>Supervisor: Prof. Monica Chiogna<br>Co-supervisor: Prof. Gianfranco Adimari<br>Date of defence: 24th March, 2017
+* October 2008 – July 2012. B.S. in Mathematics and Computer Sciences, Faculty of Mathematics and Computer Science, University of Science, Vietnam National University - Ho Chi Minh city, Vietnam.<br>Title of dissertation: *The application of nonparametric regression model for the backward heat problems*.<br>Supervisor: Prof. Dang Duc Trong
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 # Work experience
 
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 I have more than ten years of research experience in Statistics. In 2013, after graduating, I worked with Prof. Dang Duc Trong to study the application of nonparametric regression techniques for solving the backward heat problems with statistical discrete data. In 2015 and 2018, I and Prof. Duc Trong Dang, together with other colleagues, published two papers on mathematical and statistical journals.
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-In 2014, I was selected as a Ph.D. student in Statistics at the Department of Statistical Sciences with the first rank in the ranking list of CARIPARO Ph.D. scholarship at the University of Padova, Italy. During three years of my Ph.D. program, I was working on the subject "Statistical evaluation of diagnostic tests under verification bias"s which is an interested topic in Medical Statistics. In particular, I and my supervisors (Prof. Monica Chiogna and Prof. Gianfranco Adimari) have investigated several methods, both parametric and nonparametric, to correct for verification bias in the evaluation of diagnostic test accuracy when the disease status has three categories (e.g., non-diseased, intermediate, diseased). For illustration, we applied our proposed methods to evaluate the accuracy of ovarian cancer-related tumor marker CA125 (which is a highly glycosylated sialomucin that is expressed on epithelial cell surface, especially on ovarian cancer cells) and to evaluate the ability of cerebrospinal fluid tau protein to discriminate between cognitively normal and mild cognitive impairment or Alzheimer's disease. In addition, I developed an R package (named bcROCsurface) and a web interface (ShinyApps) to support researchers in the evaluation of predictive ability of diagnostic tests. As a result, I was awarded the Prize for Research 2017 of the department.
+In 2014, I was selected as a Ph.D. student in Statistics at the Department of Statistical Sciences with the first rank in the ranking list of CARIPARO Ph.D. scholarship at the University of Padova, Italy. During three years of my Ph.D. program, I was working on the subject "Statistical evaluation of diagnostic tests under verification bias" which is an interested topic in Medical Statistics. In particular, I and my supervisors (Prof. Monica Chiogna and Prof. Gianfranco Adimari) have investigated several methods, both parametric and nonparametric, to correct for verification bias in the evaluation of diagnostic test accuracy when the disease status has three categories (e.g., non-diseased, intermediate, diseased). For illustration, we applied our proposed methods to evaluate the accuracy of ovarian cancer-related tumor marker CA125 (which is a highly glycosylated sialomucin that is expressed on epithelial cell surface, especially on ovarian cancer cells) and to evaluate the ability of cerebrospinal fluid tau protein to discriminate between cognitively normal and mild cognitive impairment or Alzheimer's disease. In addition, I developed an R package (named bcROCsurface) and a web interface (ShinyApps) to support researchers in the evaluation of predictive ability of diagnostic tests. As a result, I was awarded the Prize for Research 2017 of the department.
 <br><br>
 From May 2017 to April 2018, I was a postdoctoral research fellow at the department for the project "Likelihood approaches for multivariate meta-analysis in situations with possible problems of measurements errors and missing data" under the advice of Prof. Annamaria Guolo. We developed a pseudo-likelihood approach for multivariate meta-analysis of test accuracy studies with multiple thresholds. This method is based on the ideas of composite likelihood approach and multivariate mixed-effect model. Our proposed method is applied to two real meta-analyses on the accuracy of diagnostic tests to detect significant proteinuria from pre-eclampsia of pregnancies and to identify type 2 diabetes mellitus.
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_pages/publications.md

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 You can also find full list of my publications on [Google Scholar profile.](https://scholar.google.com/citations?user=iVs_vmIAAAAJ)
 
-* Adimari, G., To. D. K., Chiogna, M., Scatozza, F. and Facchiano, A. (2023). Likelihood-type confidence regions for optimal sensitivity and specificity of a diagnostic test. *Computational Statistics and Data Analysis*. Accepted.
+* Adimari, G., To. D. K., Chiogna, M., Scatozza, F. and Facchiano, A. (2023). Likelihood-type confidence regions for optimal sensitivity and specificity of a diagnostic test. *Computational Statistics and Data Analysis*. In press. [DOI: 10.1016/j.csda.2023.107840](https://doi.org/10.1016/j.csda.2022.107434)
 
 * To. D. K., Adimari, G., and Chiogna, M. (2023). ClusROC: An R package for ROC analysis in three-class classification problems for clustered data. *The R Journal*. In press.