Prediction model of acute kidney injury induced by cisplatin in older adults using a machine learning algorithm.

Journal: PloS one
PMID: 35041690

Abstract

BACKGROUND: Early detection and prediction of cisplatin-induced acute kidney injury (Cis-AKI) are essential for the management of patients on chemotherapy with cisplatin. This study aimed to evaluate the performance of a prediction model for Cis-AKI.

Authors

  • Takaya Okawa
    Department of Clinical Pharmacy, Fujita Health University School of Medicine, Toyoake, Japan.
  • Tomohiro Mizuno
    Department of Clinical Pharmacy, Fujita Health University School of Medicine, Toyoake, Japan.
  • Shogo Hanabusa
    Department of Information Engineering, Meijo University, Nagoya, Japan.
  • Takeshi Ikeda
    Department of Information Engineering, Meijo University, Nagoya, Japan.
  • Fumihiro Mizokami
    Department of Pharmacy, National Center for Geriatrics and Gerontology, Obu, Japan.
  • Takenao Koseki
    Department of Clinical Pharmacy, Fujita Health University School of Medicine, Toyoake, Japan.
  • Kazuo Takahashi
    Department of Biomedical Molecular Sciences, Fujita Health University School of Medicine, Toyoake, Japan.
  • Yukio Yuzawa
    Department of Nephrology, Fujita Health University, Toyoake, Aichi, Japan.
  • Naotake Tsuboi
    Department of Nephrology, Fujita Health University School of Medicine, Toyoake, Japan.
  • Shigeki Yamada
    Department of Clinical Pharmacy, Fujita Health University School of Medicine, Toyoake, Japan.
  • Yoshitaka Kameya
    Department of Information Engineering, Meijo University, Nagoya, Japan.

Keywords

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