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职业迁徙
个人简介
Research interests include:
Bayesian inference of high-dimensional regression models, especially linear and generalized linear models. Together with Dr. Enes Makalic, he compiled an efficient toolbox to support the most advanced Bayesian contraction prior for high-dimensional regression models (available here);
Information theory statistics, especially the application of information theory to statistical inference through the principle of minimum message/description length;
Statistical genomics, risk prediction and mutation discovery, especially in the field of cancer genomics.
He is interested in using mammography and machine learning techniques to improve risk prediction and stratification of women's future risk of breast cancer, to assist in creating personalized screening plans.
Research area keywords
Bayesian InferenceInformation TheoryMinimum Message LengthMinimum Description LengthStatistical and Data AnalysisShrinkage EstimationStatistical genomicsCancer genomicsMammography
研究兴趣
论文共 201 篇作者统计合作学者相似作者
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Data Mining and Knowledge Discovery (2024): 1-26
John Hopper,Tuong Linh Nguyen,Michael S. Elliott,Osamah Al-qershi,Daniel F. Schmidt,Enes Makalic,Shuai Li, Samantha K. Fox,James G. Dowty,Carlos Andres Peña-Solorzano, Chun Fung Kwok,Yuanhong Chen,
crossref(2024)
GENETIC EPIDEMIOLOGY (2024)
ADVANCES IN ARTIFICIAL INTELLIGENCE, AI 2023, PT I (2024): 291-303
International Journal of Forecasting (2024)
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTIONno. 2 (2024): 306-313
Osamah Al-qershi,Tuong L Nguyen,Michael S Elliott,Daniel F Schmidt,Enes Makalic,Shuai Li, Samantha K Fox,James G Dowty,Carlos A Peña-Solorzano, Chun Fung Kwok,Yuanhong Chen,Chong Wang,
medrxiv(2024)
Roberto Biello,Silvia Ghirotto, Daniel J. Schmidt,Silvia Fuselli, David T. Roberts,Tom Espinoza, Jane M. Hughes,Giorgio Bertorelle
MOLECULAR ECOLOGYno. 5 (2024): e17266-e17266
bioRxiv : the preprint server for biology (2024)
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