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For: Al-Hindawi A, Abdulaal A, Rawson TM, Alqahtani SA, Mughal N, Moore LSP. COVID-19 Prognostic Models: A Pro-con Debate for Machine Learning vs. Traditional Statistics. Front Digit Health 2021;3:637944. [PMID: 35005694 PMCID: PMC8734592 DOI: 10.3389/fdgth.2021.637944] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 11/15/2021] [Indexed: 01/08/2023]  Open
Number Cited by Other Article(s)
1
Rusic D, Kumric M, Seselja Perisin A, Leskur D, Bukic J, Modun D, Vilovic M, Vrdoljak J, Martinovic D, Grahovac M, Bozic J. Tackling the Antimicrobial Resistance "Pandemic" with Machine Learning Tools: A Summary of Available Evidence. Microorganisms 2024;12:842. [PMID: 38792673 PMCID: PMC11123121 DOI: 10.3390/microorganisms12050842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2024] [Revised: 04/16/2024] [Accepted: 04/19/2024] [Indexed: 05/26/2024]  Open
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