Supercomputing enabling exhaustive statistical analysis of genome wide association study data: Preliminary results. - Matthias Reumann; Enes Makalic; Benjamin W. Goudey; Michael Inouye; Adrian Bickerstaffe; Minh Bui; Daniel J. Park; Miroslaw K. Kapuscinski; Daniel F. Schmidt; Zeyu Zhou; Guoqi Q. Qian; Justin Zobel; et al. (EMBC, 2012)

DEPTH: A Novel Algorithm for Feature Ranking with Application to Genome-Wide Association Studies. - Enes Makalic; Daniel F. Schmidt; John L. Hopper (Australasian Conference on Artificial Intelligence, 2013)

High performance computing enabling exhaustive analysis of higher order single nucleotide polymorphism interaction in Genome Wide Association Studies. - Benjamin Goudey; Mani Abedini; John L. Hopper; Michael Inouye; Enes Makalic; Daniel F. Schmidt; John Wagner; Zeyu Zhou; Justin Zobel; Matthias Reumann (Health Inf. Sci. Syst., 2015)

Bayesian Robust Regression with the Horseshoe+ Estimator. - Enes Makalic; Daniel F. Schmidt; John L. Hopper (Australasian Conference on Artificial Intelligence, 2016)

Approximating Message Lengths of Hierarchical Bayesian Models Using Posterior Sampling. - Daniel F. Schmidt; Enes Makalic; John L. Hopper (Australasian Conference on Artificial Intelligence, 2016)

Bayesian Grouped Horseshoe Regression with Application to Additive Models. - Zemei Xu; Daniel F. Schmidt; Enes Makalic; Guoqi Q. Qian; John L. Hopper (Australasian Conference on Artificial Intelligence, 2016)

The Ark: a customizable web-based data management tool for health and medical research. - Adrian Bickerstaffe; Thilina Ranaweera; Travis Endersby; Christopher Ellis; Sanjaya Maddumarachchi; George E. Gooden; Paul White; Eric K. Moses; Alex W. Hewitt; John L. Hopper (Bioinform., 2017)

RADIFUSION: A multi-radiomics deep learning based breast cancer risk prediction model using sequential mammographic images with image attention and bilateral asymmetry refinement. - Hong Hui Yeoh; Andrea Liew; Raphael C.-W. Phan; Fredrik Strand; Kartini Rahmat; Tuong Linh Nguyen; John L. Hopper; Maxine Tan (CoRR, 2023)