Yan Yuan, PhD (Statistics), MMath (Biostatistics), MSc (Animal Science), BSc (Biochemistry)

Contact

Associate Professor, School of Public Health

Email: yyuan@ualberta.ca
Phone: (780) 248-5853
Address: 3-299 (C05 Edmonton Clinic Health Academy
11405 - 87 Ave NW

Edmonton AB

T6G 1C9

Overview

About

My research interest is to develop and apply biostatistical methods in public health and biomedical research. Methodologically, my current interests include statistical prediction, classification and developing appropriate measures for these problems.

My current research focuses on five topics: 1) risk prediction of early menopause in childhood cancer survivors; 2) modeling individual gestational weight gain and fat accretion trajectories, and postpartum weight/fat retention; 3) developing performance measures for screening tools where prediction accuracy is assessed in a low prevalence setting; 4) rare cancer epidemiology and survivorship in Canada; 5) health services research in breast cancer screening and diagnostic care. I team up with statisticians, cancer epidemiologists, oncologists, and nutrition experts to advance our knowledge on these topics. I also work with public health researchers and professionals, and community partners to solve problems in their field.

Degrees

PhD (Statistics), University of Waterloo, 2008
MMath (Biostatistics), University of Waterloo, 2003
MSc (Animal Science), Michigan State University, 1999
BSc (Biochemistry), Nanjing University, Nanjing, China, 1996

Awards

40 under 40 young scientists, nominated by IAP - The Global Network of Science Academies, 2012
Canada Graduate Scholarship, Natural Sciences and Engineering Research Council, 2004-2007

Keywords

biostatistical methods
statistical prediction
cancer epidemiology
health services research
functional data analysis

Announcements

Supervision

Currently accepting MSc and PhD students.

Courses

SPH 547 - Public Health Practice Project

Building on Public Health Practice & Professional Skills I & II, students continue to practice and strengthen professional competencies by working in teams assigned to external partner organizations to address a complex public health challenge. Organizations' priority projects may emphasize any stage of the assessment-planning-action-evaluation cycle. This course emphasizes professional skills - effective teamwork, reflection and peer assessment, oral and written communication; and project management including terms of engagement, a project charter and work plan, and high-quality deliverables. SPH 547 is a required course for the degree of Master of Public Health in General Public Health. Pre-requisites: SPH 530, SPH 535, SPH 536, SPH 537, SPH 541, SPH 546, SPH 562, SPH 563, or consent of instructor.

Fall Term 2023

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Scholarly Activities

Research - Brain Tumour Registry of Canada

2016 to 2019

Co-investigator
Funded by Brain Canada

Research - Gestational Diabetes Management and its Influence on Breastfeeding Practices

2018 to 2019

Co-investigator
Funded by Canadian Institutes of Health Research

Research - Maternal Iron Nutrition and its Consequences in Pregnant Women and Their Children in the Alberta Pregnancy Outcomes and Nutrition Study

2018 to 2021

Co-investigator
Funded by Canadian Institutes of Health Research

Research - Optimizing Outcomes in Survivors of Childhood, Adolescent and Young Adult Cancer

2018 to 2026

Co-investigator
Funded by Canadian Institutes of Health Research

Research - Performance Measures and Models for Statistical Prediction

Principal investigator
Funded by Natural Sciences and Engineering Research Council (NSERC

Research - Risk Prediction for Premature Ovarian Insufficiency in Childhood Cancer Survivors

2016 to 2021

Primary investigator
Funded by the Canadian Institutes of Health Research

The impact of false positive breast cancer screening mamograms on screening retention: A retrospective population cohort study in Alberta, Canada"

Ye Shen, Marcy Winget, Yan Yuan

Canadian Journal of Public Health. 2017 January; Vol 108(2017)

Trajectory modeling of gestational weight: a function principal component analysis approach

Che M, Kong L, Bell RC, Yuan Y

PLoS One(2017). 2017 January;

Using administrative data to estimate time to breast cancer diagnosis and percent of screen‐detected breast cancers – a validation study in Alberta, Canada

Y. Yuan, M. Li, J. Yang, M. Winget

European Journal of Cancer Care. 2014 January;

The index lift in data mining has a close relationship with the association measure relative risk in epidemiological studies

Khanh Vu, Rececca A. Clark, Colin Belinger, Graham Erickson, Alvaro Orsinio-Vargas, Osmar R. Zaiane, Yan Yuan

BMC.