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Machine learning: applications of artificial intelligence to imaging and diagnosis

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Abstract

Machine learning (ML) is a form of artificial intelligence which is placed to transform the twenty-first century. Rapid, recent progress in its underlying architecture and algorithms and growth in the size of datasets have led to increasing computer competence across a range of fields. These include driving a vehicle, language translation, chatbots and beyond human performance at complex board games such as Go. Here, we review the fundamentals and algorithms behind machine learning and highlight specific approaches to learning and optimisation. We then summarise the applications of ML to medicine. In particular, we showcase recent diagnostic performances, and caveats, in the fields of dermatology, radiology, pathology and general microscopy.

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Correspondence to Matthew A. B. Baker.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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This article is part of a Special Issue on ‘Big Data’ edited by Joshua WK Ho and Eleni Giannoulatou

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Nichols, J.A., Herbert Chan, H.W. & Baker, M.A.B. Machine learning: applications of artificial intelligence to imaging and diagnosis. Biophys Rev 11, 111–118 (2019). https://doi.org/10.1007/s12551-018-0449-9

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  • DOI: https://doi.org/10.1007/s12551-018-0449-9

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