Evolution of clinical and diagnostic microbiology in the era of artificial intelligence: a narrative review

BackgroundArtificial intelligence (AI) is an upcoming field that focuses on the evolution of intelligent machines which can easily perform labor intensive tasks with great accuracy. It has the ability to promptly analyze large amounts of data in a short span of time due to which it has been used for pathogen identification, and to make predictions regarding culture plate interpretations in a clinical specimen. This study reviews AI’s impact on clinical microbiology, focusing on microorganism identification, antimicrobial resistance detection, drug development, and record management, while highlighting key challenges. MethodsA systematic review was conducted until June 1, 2024 by searching literature from various databases such as PubMed, Scopus, Web of Science, and manual search using keywords ‘AI and clinical microbiology’, ‘AI and diagnostic microbiology’, ‘AI and microscopy’, ‘AI and antimicrobial resistance’. Only the articles focusing on the use of AI in clinical or diagnostic microbiology were included and others were excluded. As the involvement of AI in clinical microbiology is a relatively recent and upcoming modality, majority of the selected articles were published in the last 5 years only. ResultsAI algorithms can be used for pathogen identification, bacterial growth detection, microscopy, colony counting, antimicrobial susceptibility testing, and maintenance of electronic records in a clinical microbiology laboratory. This review focuses on the various AI algorithms that are relevant for clinical microbiology, some of which have already been used in pilot studies in many developed countries. ConclusionWith the increasing number of publications on the use of AI in clinical microbiology, education and training regarding these technological advancements has become indispensable.