Potential roles for artificial intelligence in clinical microbiology from improved diagnostic accuracy to solving the staffing crisis.

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS

ACS Applied Bio Materials Pub Date : 2024-08-13 DOI:10.1093/ajcp/aqae107

Erin Graf, Amr Soliman, Mohamed Marouf, Anil V Parwani, Preeti Pancholi

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引用次数: 0

Abstract

Objectives: This review summarizes the current and potential uses of artificial intelligence (AI) in the current state of clinical microbiology with a focus on replacement of labor-intensive tasks.

Methods: A search was conducted on PubMed using the key terms clinical microbiology and artificial intelligence. Studies were reviewed for relevance to clinical microbiology, current diagnostic techniques, and potential advantages of AI in routine microbiology workflows.

Results: Numerous studies highlight potential labor, as well as diagnostic accuracy, benefits to the implementation of AI for slide-based and macroscopic digital image analyses. These range from Gram stain interpretation to categorization and quantitation of culture growth.

Conclusions: Artificial intelligence applications in clinical microbiology significantly enhance diagnostic accuracy and efficiency, offering promising solutions to labor-intensive tasks and staffing shortages. More research efforts and US Food and Drug Administration clearance are still required to fully incorporate these AI applications into routine clinical laboratory practices.

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人工智能在临床微生物学中的潜在作用，从提高诊断准确性到解决人员危机。

目的本综述总结了人工智能（AI）在临床微生物学现状中的当前和潜在用途，重点是替代劳动密集型任务：方法：在 PubMed 上以临床微生物学和人工智能为关键词进行搜索。方法：使用临床微生物学和人工智能这两个关键词在PubM上进行了搜索，审查了与临床微生物学相关的研究、当前的诊断技术以及人工智能在常规微生物学工作流程中的潜在优势：结果：大量研究强调了人工智能在基于幻灯片和宏观数字图像分析中的潜在优势，包括劳动力和诊断准确性。这些优势包括从革兰氏染色解读到培养生长的分类和量化：人工智能在临床微生物学中的应用大大提高了诊断的准确性和效率，为解决劳动密集型任务和人员短缺问题提供了有前途的解决方案。要将这些人工智能应用完全纳入常规临床实验室实践，还需要更多的研究工作和美国食品药品管理局的批准。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

ACS Applied Bio Materials Chemistry-Chemistry (all)

CiteScore

9.40

自引率

2.10%

发文量

464