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Enhancing rapid microbiology methods: how AI is shaping microbiology

Rapid microbiological methods are being enhanced by artificial intelligence (machine learning in particular). The aim is to speed up analysis; increase accuracy; avoid error and introduce a level of automation. Examples include microscopy, colony counting, and microbial characterisation and matching – each of which is based on improvements in image analysis. Bio Products Laboratory’s Dr Tim Sandle explores further.

ARTIFICIAL INTELLIGENCE (AI), or more specifically machine learning (ML), is used in many aspects of microbiology research, including microbial classification problems, studying the interaction between microorganisms and the surrounding environment, and for microscopy. This article reviews some recent developments in this emerging field. While more progress has been made in the clinical microbiology space, these emerging technologies have the potential to re-shape aspects of rapid microbiology within the pharmaceutical and healthcare sectors too.