Using large administrative data for mining patients’ trajectories for risk stratification: An example from urological diseases

• Harvey Jia Wei Koh,

  Roles Conceptualization, Data curation, Formal analysis, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing

  Affiliations Centre for Learning Analytics, Faculty of Information Technology, Monash University, Clayton, Australia, Digital Health Cooperative Research Centre, Sydney, Australia, School of Public Health and Preventative Medicine, Monash University, Melbourne, Australia

  https://orcid.org/0000-0002-4304-2783

  ⨯
• Dragan Gašević,

  Roles Formal analysis, Supervision, Writing – original draft, Writing – review & editing

  Affiliations Centre for Learning Analytics, Faculty of Information Technology, Monash University, Clayton, Australia, Digital Health Cooperative Research Centre, Sydney, Australia

  ⨯
• David Rankin,

  Roles Data curation, Supervision, Writing – original draft, Writing – review & editing

  Affiliations Digital Health Cooperative Research Centre, Sydney, Australia, Cabrini Healthcare, Malvern, Australia

  ⨯
• Mark Frydenberg,

  Roles Supervision, Writing – original draft, Writing – review & editing

  Affiliations Department of Surgery, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia, Cabrini Institute, Cabrini Healthcare, Malvern, Australia

  ⨯
• Stella Talic

  Roles Conceptualization, Methodology, Supervision, Writing – original draft, Writing – review & editing

  * E-mail: stella.talic@monash.edu

  Affiliations Digital Health Cooperative Research Centre, Sydney, Australia, School of Public Health and Preventative Medicine, Monash University, Melbourne, Australia

  ⨯