Machine learning models of healthcare expenditures predicting mortality: A cohort study of spousal bereaved Danish individuals

• Alexandros Katsiferis ,

  Roles Conceptualization, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing

  * E-mail: alexandros.katsiferis@sund.ku.dk

  Affiliations Section for Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark, Statistics Denmark, Denmark

  https://orcid.org/0000-0002-0957-9835

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• Samir Bhatt,

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

  Affiliations Section for Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom

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• Laust Hvas Mortensen,

  Roles Data curation, Investigation, Methodology, Writing – original draft, Writing – review & editing

  Affiliations Section for Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark, Statistics Denmark, Denmark

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• Swapnil Mishra,

  Roles Investigation, Methodology, Writing – original draft, Writing – review & editing

  Affiliations Section for Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark, Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore

  https://orcid.org/0000-0002-8759-5902

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• Majken Karoline Jensen,

  Roles Investigation, Methodology, Writing – original draft, Writing – review & editing

  Affiliations Section for Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark, Statistics Denmark, Denmark

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• Rudi G. J. Westendorp

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

  Affiliation Section for Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark

  https://orcid.org/0000-0002-0672-8372

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