aceAutomation and artificial intelligence in the clinical microbiology laboratory
Background Clinical microbiology laboratories face persistent pressure to shorten turnaround times, reduce manual workloads, and standardize diagnostic workflows. Total laboratory automation (TLA) and artificial intelligence (AI) are complementary responses to these demands. In this review, we examine how the evidence base for automation and AI in clinical microbiology is distributed along a maturity gradient and what this distribution implies for the next phase of implementation. Content Available evidence indi…
Automated microbiology platforms shorten culture turnaround times and reduce manual workload, with automated reading, identification, and susceptibility systems agreeing closely with manual standards.
Most AI models for plate reading and resistance prediction remain assistive without prospective validation, and randomized trials rarely show clinical superiority or consistent patient-oriented benefit.
Most AI models lack prospective validation, patient-oriented benefits are limited and inconsistent, and the review describes AI-assisted evidence tools as preliminary.
Evidence
- Peer-reviewedFrontiers in Cellular and Infection Microbiology2026-10-20
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Truvace Impact Record TRV-2026-2096, v1: “Automation and artificial intelligence in the clinical microbiology laboratory.” Truvace, 2026-10-21. /record/TRV-2026-2096 (accessed at citation time). sha256 478d169e6a27100f…
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