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© 2020 Artificial intelligence (AI) is at the forefront of modern technology and emerging uses within the healthcare sector are now being realised. Pathology will be a key area where the impact of AI will be felt. With more and more laboratories making the transition to digital pathology this will provide the key infrastructure in which to deploy these tools and their use will start to become a reality in diagnostic practice. The potential of AI in pathology is to create image analysis tools which could either be used for diagnostic support or to derive novel insights into disease biology, in addition to those achievable with a human observer. Some examples providing diagnostic support currently exist for a limited, but expanding number of applications, such as tumour detection, automated tumour grading, immunohistochemistry scoring, and predicting mutation status. There are a number of challenges to consider, not least the validation and regulatory framework for these tools. In this article, we set out an overview of AI in histopathology, discuss its potential workflow applications, and give key examples of the potential for AI in clinical practice. Considerations for the implementation of AI in practice are also explored.

Original publication




Journal article


Diagnostic Histopathology

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