Centre for Data Analytics

Research output

Research output per year 1986 2018 2020 2021 2022 2023 2024 2024

• 3161 Citations
• 28 h-index
• 204 Article
• 34 Abstract
• 31 Conference contribution
• 21 Chapter
• 107 More
  • 20 Comment/debate/opinion
  • 17 Presentation
  • 16 Book/Film/Article review
  • 11 Paper
  • 5 Scholarly edition
  • 5 Poster
  • 5 Review article
  • 4 Meeting Abstract
  • 3 Other chapter contribution
  • 3 Magazine Article
  • 3 Software
  • 2 Book
  • 2 Digital or Visual Products
  • 2 Discipline Preprint Repository
  • 1 Other report
  • 1 Foreword/postscript
  • 1 Other
  • 1 Editorial
  • 1 Special issue
  • 1 Featured article
  • 1 Other contribution
  • 1 Submission to government
  • 1 Patent

Research output per year

Research output per year

Search results

• 2023

  Automated coding of suicidal ideation in emergency department presentations: balancing interpretability and performance

  Todd, J., Gepp, A., Hudson, C. & Randall, M., Sept 2023, p. 1-1. 1 p.

  Research output: Contribution to conference › Abstract › Research

  Open Access

  • Embeddings (Algorithms) 100%
  • Health 60%
  • Logistic regression 46%
  • Coastal zones 45%
  • Gold 44%

• Day to day glycemic variability using continuous glucose monitors in trained endurance athletes.

  Bowler, A-L., Burke, L. M., Coffey, V. G. & Cox, G. R., 23 Oct 2023.

  Research output: Contribution to conference › Abstract › Research › peer-review

  Open Access

  • Athletes 100%
  • Glucose 69%
  • Exercise 35%
  • Carbohydrates 31%
  • Glycemic Index 24%

• Garbage In Garbage Out: Test-Retest Reliability of Spectral Parameterization by FOOOF: Proceedings of Society for Psychophysiological Research Annual Meeting 2023

  Angus, D., McKeown, D., Schinazi, V. R., Baumann, O., Moustafa, A. A., Finley, A., Kelley, N., Cavanagh, J. & Keage, H., 1 Sept 2023, p. S74. 1 p.

  Research output: Contribution to conference › Abstract › Research › peer-review

  Open Access

  • Reproducibility of Results 100%
  • Eye 69%
  • Episodic Memory 31%
  • Music 31%
  • Psychological Power 26%

• Match-play data-driven player positions within the Australian Football League Women’s competition

  Van der Vegt, B., Gepp, A., Keogh, J. W. L. & Farley, J. B., 25 May 2023, p. 76-76. 1 p.

  Research output: Contribution to conference › Abstract › Research › peer-review

  • Football 100%
  • Data reduction 20%
  • Random forests 18%
  • Principal component analysis 16%
  • Clustering algorithms 15%

• Towards More Nuanced Patient Management: Decomposing Readmission Risk with Survival Models

  Todd, J. & Stern, S., 6 Sept 2023, p. 157-158. 2 p.

  Research output: Contribution to conference › Abstract › Research

  Open Access

  File

  • Survival 100%
  • Calibration 53%
  • Queensland 32%
  • Ghana 31%
  • Patient Readmission 29%
  218 Downloads (Pure)
• 2022

  Globally transforming researcher development through micro-credentials

  Gill, C., Mehrotra, V. & Faff, R. W., Nov 2022, (Unpublished).

  Research output: Contribution to conference › Abstract › Research › peer-review

  File

  • university research 100%
  • educational research 82%
  • educational offerings 64%
  • career 55%
  • market 48%
  46 Downloads (Pure)

• Performance analysis in women's Australian football: A review of current literature, challenges, and its potential for future research

  Van der Vegt, B., Farley, J. B., Gepp, A. & Keogh, J. W. L., Feb 2022.

  Research output: Contribution to conference › Abstract › Research › peer-review

  Open Access

  File

  • performance 100%
  • literature 90%
  • sports science 89%
  • Sports 87%
  • best practice 38%
  66 Downloads (Pure)

• The significance of Occupation on Socio-demographic and Lifestyle-related risk factors in the development of AD

  Ahmed, T., Kumar, K. & Zhang, P., 2 Nov 2022, p. 36.

  Research output: Contribution to conference › Abstract › Research › peer-review

  Open Access

  • dementia 100%
  • occupation 79%
  • occupational group 34%
  • manager 30%
  • modern times 18%
• 2021

  Moral Disengagement, Neutralization Techniques, and (Un)ethical Consumer Behaviour

  McCormack, R., Chowdhury, R. & Rajaguru, G., 29 Nov 2021, p. 347.

  Research output: Contribution to conference › Abstract › Research › peer-review

  Open Access

  • Consumer Behaviour 100%
  • Locus of Control 64%
  • Cynicism 61%
  • Traits 42%
  • Ethical Consumption 41%
• 2020

  Alzheimer’s Disease: Identifying High Impact Variables Using Statistical Techniques

  Ahmed, T., Kumar, K. & Zhang, P., Jun 2020, (Unpublished) p. 5.

  Research output: Contribution to conference › Abstract › Research › peer-review

  File

  • Brain 100%
  • Neuroimaging 79%
  • Logistic regression 67%
  • Random forests 63%
  • Decision trees 58%
  66 Downloads (Pure)

• Bankruptcy Prediction of Australian SMEs and Large Companies

  Halteh, K., Gepp, A. & Kumar, K., Jun 2020, (Unpublished).

  Research output: Contribution to conference › Abstract › Research › peer-review

  File

  • Small and Medium-sized Enterprises (SMEs) 100%
  • Bankruptcy Prediction 85%
  • Large Companies 60%
  • Machine Learning 37%
  • Minorities 29%
  64 Downloads (Pure)

• Control chart for mean and standard deviation for observation following SAR (1,1) process

  Srivastava, A., Kumar, K. & Chaturvedi, A., Jun 2020, p. 7.

  Research output: Contribution to conference › Abstract › Research

  • Mean deviation 100%
  • Control Charts 83%
  • Standard deviation 82%
  • Observation 51%
  • Spatial Process 17%

• Did Herschelle Gibbs Really Drop the 1999 Cricket World Cup: and other uses of the Duckworth-Lewis Methodology

  Stern, S., 12 Nov 2020, p. 37.

  Research output: Contribution to conference › Abstract › Research › peer-review

  Open Access

  • cricket 100%
  • ranking 43%
  • methodology 39%
  • world 39%
  • resetting 29%

• Money Laundering: Using a hybrid approach to detect illicit shell companies

  Tiwari, M., Gepp, A. & Kumar, K., Jun 2020, p. 35.

  Research output: Contribution to conference › Abstract › Research › peer-review

  Open Access

  File

  • money laundering 100%
  • network analysis 15%
  • learning 10%
  • transparency 6%
  • time 5%
  97 Downloads (Pure)

• Producing actionable data-driven insights to improve athlete and team performance

  Van der Vegt, B., Gepp, A., Johnman, M. & Vanstone, B. J., Feb 2020.

  Research output: Contribution to conference › Abstract › Research › peer-review

  Open Access

  File

  • Sports 100%
  • Competitive intelligence 41%
  • Predictive analytics 21%
  • Data Analytics 18%
  • Machine learning 12%
  81 Downloads (Pure)
• 2019

  Using Customer Information and Bayesian Techniques to Enhance Persistence Modelling

  Johnman, M., Gepp, A. & Vanstone, B. J., Jun 2019, p. 87.

  Research output: Contribution to conference › Abstract › Research › peer-review

  • Customer Information 100%
  • Persistence 76%
  • Modeling 47%
  • Marketing Effectiveness 42%
  • Marketing 19%
• 2018

  The Financial Consequence of Integrity: Using Automated Fraud Detection for Investment

  Yee, A., Gepp, A., Kumar, K. & Vanstone, B. J., 2018.

  Research output: Contribution to conference › Abstract › Research

  • Fraud Detection 100%
  • Financial Statement Fraud 76%
  • Integrity 72%
  • Portfolio Performance 62%
  • Fraud 49%
• 2017

  Big Data and ICU Scoring Systems

  Todd, J., Gepp, A., Vanstone, B. J. & Richards, B., 2017, p. 47-48. 2 p.

  Research output: Contribution to conference › Abstract › Research › peer-review

  Open Access

  • health status 100%
  • gold 22%
  • calibration 22%
  • statistics 21%
  • physiology 18%

• Financial Distress Prediction in the Australian Mining Industry using Tree-Based Stochastic Techniques

  Halteh, K., Gepp, A. & Kumar, K., Nov 2017.

  Research output: Contribution to conference › Abstract › Research › peer-review

  • Financial Distress 100%
  • Mining Industry 99%
  • Prediction 76%
  • Gradient 68%
  • Boosting 64%

• Role of fiscal consolidation in vulnerability to crisis: Evidence from Australian economy

  Ur-Rahman, H., Goldsmith, A., Rajaguru, G. & Khan, S., 2017.

  Research output: Contribution to conference › Abstract › Research › peer-review

  • Fiscal Consolidation 100%
  • Public Debt 82%
  • Vulnerability 72%
  • Capital Adequacy Ratio 35%
  • Financial Sector 24%
• 2016

  Addressing the problem of financial statement fraud: Better detection through improved models

  Gepp, A., 2016.

  Research output: Contribution to conference › Abstract › Research › peer-review

  • Financial Statement Fraud 100%
  • Fraud Detection 87%
  • Fraud 27%
  • Variable Selection 17%
  • Factors 13%

• Detecting fraud in corporate financial statements using trees and forests

  Kumar, K., Gepp, A. & Bhattacharya, S., 2016.

  Research output: Contribution to conference › Abstract › Research › peer-review

• Evaluating the threat posed by quantum computing to the security of online business systems

  Harris, G. & Gepp, A., 2016.

  Research output: Contribution to conference › Abstract › Research › peer-review

  • quantum mechanics 100%
  • mechanics 30%
  • accounting system 24%
  • immune system 21%
  • history 18%

• Financial distress prediction using cutting-edge statistical techniques

  Halteh, K., Gepp, A. & Kumar, K., 2016.

  Research output: Contribution to conference › Abstract › Research › peer-review

  • Industry 100%
  • Random forests 30%
  • Decision trees 27%
  • Statistical Models 26%

• Improved models to detect fraud in financial statements

  Gepp, A., Kumar, K. & Bhattacharya, S., 2016.

  Research output: Contribution to conference › Abstract › Research › peer-review

  • cost 100%
  • decision 73%
  • detection 67%
  • logistics 33%
  • stakeholder 30%

• Improving models that detect financial statement fraud: A new framework to guide variable selection

  Gepp, A., Kumar, K. & Bhattacharya, S., 2016.

  Research output: Contribution to conference › Abstract › Research › peer-review

  • Variable Selection 100%
  • Financial Statement Fraud 82%
  • Fraud Detection 48%
  • Selection Process 18%
  • Fraud 17%

• The fraud detection triangle: A new framework for fraud detection research

  Gepp, A., Kumar, K. & Bhattacharya, S., 2016.

  Research output: Contribution to conference › Abstract › Research › peer-review
• 2015

  A new framework for selecting variables in fraud detection research

  Gepp, A. & Kumar, K., 2015, p. 1-1. 1 p.

  Research output: Contribution to conference › Abstract › Research › peer-review

  • Fraud Detection 100%
  • Fraud 74%
  • Financial Statement Fraud 17%
  • Common Factors 7%
  • Conceptual Model 7%

• A real options approach to valuing agricultural resource assets under uncertainty: US corn crops

  Smith, M., Kelly, S. & McNamara, R., 2015, p. 1-1. 1 p.

  Research output: Contribution to conference › Abstract › Research › peer-review

  • Corn 100%
  • Crops 84%
  • Real Options 82%
  • Resources 52%
  • Uncertainty 48%

• Bankruptcy prediction using industry-specific variables

  Halteh, K. & Kumar, K., 2015. 1 p.

  Research output: Contribution to conference › Abstract › Research › peer-review

  • Bankruptcy Prediction 100%
  • Business Failures 47%
  • Failure Prediction 27%
  • Industry 26%
  • Ratio Analysis 24%

• The fraud detection triangle: A new framework for selecting variables in fraud detection research

  Gepp, A., Kumar, K. & Bhattacharya, S., 2015.

  Research output: Contribution to conference › Abstract › Research › peer-review

  • Fraud Detection 100%
  • Financial Statement Fraud 38%
  • Fraud 24%
  • Selection Process 12%
• 2014

  Financial distress prediction: A cost-sensitive study using accounting ratios that compares multiple modelling techniques

  Gepp, A. & Kumar, K., 2014.

  Research output: Contribution to conference › Abstract › Research › peer-review

• Using decision trees to detect financial statement fraud

  Gepp, A. & Kumar, K., 2014.

  Research output: Contribution to conference › Abstract › Research
• 2012

  Financial distress prediction using decision trees and survival analysis

  Gepp, A. & Kumar, K., 2012.

  Research output: Contribution to conference › Abstract › Research › peer-review