Usability of machine learning algorithms based on electronic health records for the prediction of acute kidney injury and transition to acute kidney disease: A proof of concept study

• Lorenzo Ruinelli,

  Roles Conceptualization, Data curation, Formal analysis, Writing – original draft

  Affiliations Area ICT, Ente Ospedaliero Cantonale, Bellinzona, Switzerland, Clinical Trial Unit, Ente Ospedaliero Cantonale, Bellinzona, Switzerland

  https://orcid.org/0000-0002-9144-2570

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• Pietro Cippà,

  Roles Writing – review & editing

  Affiliations Division of Nephrology, Ente Ospedaliero Cantonale, Lugano, Switzerland, Faculty of Biomedical Sciences, Università della Svizzera italiana, Lugano, Switzerland

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• Chantal Sieber,

  Roles Writing – original draft, Writing – review & editing

  Affiliation Division of Nephrology, Ente Ospedaliero Cantonale, Lugano, Switzerland

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• Clelia Di Serio,

  Roles Supervision, Writing – review & editing

  Affiliation Clinical Trial Unit, Ente Ospedaliero Cantonale, Bellinzona, Switzerland

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• Paolo Ferrari,

  Roles Writing – review & editing

  Affiliations Department of Medicine, Ente Ospedaliero Cantonale, Bellinzona, Switzerland, Clinical School, University of New South Wales, Sydney, Australia

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• Antonio Bellasi

  Roles Conceptualization, Methodology, Supervision, Writing – original draft

  * E-mail: antonio.bellasi@eoc.ch, antonio.bellasi@usi.ch

  Affiliations Division of Nephrology, Ente Ospedaliero Cantonale, Lugano, Switzerland, Faculty of Biomedical Sciences, Università della Svizzera italiana, Lugano, Switzerland

  https://orcid.org/0000-0001-7830-1645

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