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Weiva Sieh, MD, PhD, MS
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About Me
Dr. Sieh’s research focuses on identifying genetic and epidemiologic factors underlying cancer susceptibility and outcomes. Current interests include:
1) Genetic and environmental determinants of mammographic breast density; relationship of breast density and other image features to breast cancer risk.
2) Genomic risk prediction using machine learning methods.
3) Risk and prognosis of hormone-related cancers, including cancers of the breast, ovary and prostate.
Language
Position
About Me
Dr. Sieh’s research focuses on identifying genetic and epidemiologic factors underlying cancer susceptibility and outcomes. Current interests include:
1) Genetic and environmental determinants of mammographic breast density; relationship of breast density and other image features to breast cancer risk.
2) Genomic risk prediction using machine learning methods.
3) Risk and prognosis of hormone-related cancers, including cancers of the breast, ovary and prostate.
Language
Position
About Me
Dr. Sieh’s research focuses on identifying genetic and epidemiologic factors underlying cancer susceptibility and outcomes. Current interests include:
1) Genetic and environmental determinants of mammographic breast density; relationship of breast density and other image features to breast cancer risk.
2) Genomic risk prediction using machine learning methods.
3) Risk and prognosis of hormone-related cancers, including cancers of the breast, ovary and prostate.
Language
Position
Education
BA Biology, Harvard University
MD Medicine, McGill University
MS Biostatistics, University of Washington
PhD Epidemiology, University of Washington
Postdoc Statistical Genetics, University of Washington
Locations
Publications
Selected Publications
- MiXcan: a framework for cell-type-aware transcriptome-wide association studies with an application to breast cancer
- Lifetime ovulatory years and risk of epithelial ovarian cancer: a multinational pooled analysis
- Factors that influence treatment decisions: A qualitative study of racially and ethnically diverse patients with low- and very-low risk prostate cancer
- Adverse pregnancy outcomes and long term risk of ischemic heart disease in mothers: national cohort and co-sibling study
- Long-term Risks of Depression and Suicide Among Men with Prostate Cancer: A National Cohort Study
- Ovarian cancer pathology characteristics as predictors of variant pathogenicity in BRCA1 and BRCA2
- Genome-wide and transcriptome-wide association studies of mammographic density phenotypes reveal novel loci
- Copy number variants are ovarian cancer risk alleles at known and novel risk loci
- Risks of Depression and Suicide After Diagnosis With Heart Failure: A National Cohort Study
- Erratum: Correction: Polygenic risk modeling for prediction of epithelial ovarian cancer risk (European journal of human genetics : EJHG (2022) 30 3 (349-362))
Industry Relationships
Physicians and scientists on the faculty of the Icahn School of Medicine at Mount Sinai often interact with pharmaceutical, device and biotechnology companies to improve patient care, develop new therapies and achieve scientific breakthroughs. In order to promote an ethical and transparent environment for conducting research, providing clinical care and teaching, Mount Sinai requires that salaried faculty inform the School of their relationships with such companies.
Dr. Sieh did not report having any of the following types of financial relationships with industry during 2022 and/or 2023: consulting, scientific advisory board, industry-sponsored lectures, service on Board of Directors, participation on industry-sponsored committees, equity ownership valued at greater than 5% of a publicly traded company or any value in a privately held company. Please note that this information may differ from information posted on corporate sites due to timing or classification differences.
Mount Sinai's faculty policies relating to faculty collaboration with industry are posted on our website. Patients may wish to ask their physician about the activities they perform for companies.