Machine learning algorithms to predict colistin-induced nephrotoxicity from electronic health records in patients with multidrug-resistant Gram-negative infection.

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Bibliographic Details
Title: Machine learning algorithms to predict colistin-induced nephrotoxicity from electronic health records in patients with multidrug-resistant Gram-negative infection.
Authors: Chiu LW; Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan; Department of Pharmacy, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan., Ku YE; Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan., Chan FY; Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan., Lie WN; Department of Electrical Engineering, National Chung Cheng University, Chiayi, Taiwan., Chao HJ; Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan., Wang SY; Pharmacogenomics and Pharmacoproteomics, College of Pharmacy, Taipei Medical University, Taipei, Taiwan., Shen WC; Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan; Department of Pharmacy, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan., Chen HY; Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan; Department of Pharmacy, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan. Electronic address: shawn@tmu.edu.tw.
Source: International journal of antimicrobial agents [Int J Antimicrob Agents] 2024 Jul; Vol. 64 (1), pp. 107175. Date of Electronic Publication: 2024 Apr 19.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Science Publishers Country of Publication: Netherlands NLM ID: 9111860 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1872-7913 (Electronic) Linking ISSN: 09248579 NLM ISO Abbreviation: Int J Antimicrob Agents Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1872-7913
DOI:10.1016/j.ijantimicag.2024.107175