Detecting anomalous matches in professional sports: a novel approach using advanced anomaly detection techniques
Detecting anomalous matches in professional sports: a novel approach using advanced anomaly detection techniques
Accounting for Errors in Data Improves Divergence Time Estimates in Single-cell Cancer Evolution
Reconstruct the phylogenetic history of a colorectal cancer patient and a healthy patient from single-cell DNA sequencing data.
Improving In Vitro Fertilisation (IVF) with Machine and Deep Learning
By exploring how to improve the success rate of In Vitro Fertilisation (IVF) implantations, we hope the knowledge will be embedded in a model and made it widerly available locally and overseas where the investment will generate export value for New Zealand and benefit the needed parents by reducing IVF waiting time and increasing the rate of live births.
Rapid monitoring of infrastructural health using remote sensing
Research digital skills training 2021 Rapid monitoring of infrastructural health using remote sensing Dr Lucas Hogan. Lecturer, Dr Max Stephens, Lecturer, Civil and Environmental Engineering, Dr Chris Seal, Centre for eResearch Home • Archive for "case...
Proteins under a computational microscope: designing in-silico strategies to understand and develop molecular functionalities in Life Sciences and Engineering
A key factor regulating molecular function is molecular dynamics…
Genomic Virtual Lab (GVL) as a bioinformatics training platform
Genomic Virtual Lab (GVL) as a bioinformatics training platform Peter Tsai, PhD Candidate, Dr Thierry Jean Lints, Professional Teaching Fellow, Professor Cristin Print, Molecular Medicine and Pathology; Dr William Schierding, Research Fellow, Liggins Institute...
Myocardial motion tracking and strain calculation using Deep Learning networks
Myocardial motion tracking and strain calculation using Deep Learning networks Edward Ferdian, Dr Avan Suinesiaputra and Professor Alistair Young, Department of Anatomy and Medical Imaging, Faculty of Medical and Health Sciences Home • Archive for...
OnTask pilot at the Centre for Learning and Research in Higher Education
OnTask is the latest open source iteration of the Student Relationship and Engagement System (SRES) initially created at the University of Sydney. A second, open source version of SRES was initiated in 2015 as a joint effort between the universities of Sydney, Auckland and Otago supported by a nationally funded project from Ako Aotearoa NZ.
