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Increased healthcare demand has placed pressure on laboratory medicine to improve turnover and optimise efficiency using digitalisation, automation and artificial intelligence (AI). This will bring new challenges for the clinical laboratory. Laboratorians need to understand the utility of AI, its limitations and implementation. The management of big data requires ready access and accurate and contextual analysis. AI uses complex algorithms and data from medical and laboratory data to mimic human analysis and this requires accurate and reliable data. The role of AI in laboratory medicine is rapidly expanding owing to recognition of its potential to improve detection, laboratory workflows, decision support and reduce costs and increase efficiency. In this thematic issue on AI, we have attempted to present an overview of the uses of AI in laboratory medicine and advances in the digitalisation of pathology.
Rakha et al 1 from the University of Nottingham and Google Health provide an erudite overview of current and future applications of AI in pathology. The applications of AI in pathology range from prognostic/predictive applications to workflow and diagnostic …
Handling editor Runjan Chetty.
Funding The author has not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Provenance and peer review Commissioned; internally peer reviewed.
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