根据致病微生物对尿培养结果进行尿液分析的预测性能:人工智能综合分析

IF 6.1 2区 医学 Q1 MICROBIOLOGY Journal of Clinical Microbiology Pub Date : 2024-09-12 DOI:10.1128/jcm.01175-24
Min Hyuk ChoiDokyun KimHye Gyung BaeAe-Ran KimMikyeong LeeKyungwon LeeKyoung-Ryul LeeSeok Hoon Jeong1Department of Laboratory Medicine and Research Institute of Bacterial Resistance, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea2Seoul Clinical Laboratories, Yongin-si, South KoreaErin McElvania
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引用次数: 0

摘要

临床微生物学杂志》,提前出版。
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Predictive performance of urinalysis for urine culture results according to causative microorganisms: an integrated analysis with artificial intelligence
Journal of Clinical Microbiology, Ahead of Print.
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来源期刊
Journal of Clinical Microbiology
Journal of Clinical Microbiology 医学-微生物学
CiteScore
17.10
自引率
4.30%
发文量
347
审稿时长
3 months
期刊介绍: The Journal of Clinical Microbiology® disseminates the latest research concerning the laboratory diagnosis of human and animal infections, along with the laboratory's role in epidemiology and the management of infectious diseases.
期刊最新文献
Characterization of carbapenem-resistant Enterobacterales and Pseudomonas aeruginosa carrying multiple carbapenemase genes-Antimicrobial Resistance Laboratory Network, 2018-2022. A simplified pyrazinamidase test for Mycobacterium tuberculosis pyrazinamide antimicrobial susceptibility testing. Retrospective analysis of antimicrobial susceptibility profiles of non-diphtheriae Corynebacterium species from a tertiary hospital and reference laboratory, 2012-2023. Performance evaluation of the Specific Reveal system for rapid antibiotic susceptibility testing from positive blood cultures containing Gram-negative pathogens. Evaluation of the KPC/IMP/NDM/VIM/OXA-48 Combo Test Kit and Carbapenem-Resistant K.N.I.V.O. Detection K-Set in detecting KPC variants.
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