COMMENT CSJ THE CLINICAL SERVICES JOURNAL Editor


Chris Shaw chrisshaw@stepcomms.com


Technical Editor Kate Woodhead


Business Manager Dean Walford deanwalford@stepcomms.com


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Rob Cornish robcornish@stepcomms.com


Journal Administration Katy Cockle katycockle@stepcomms.com


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Publisher


Geoff King geoffking@stepcomms.com


Publishing Director Trevor Moon trevormoon@stepcomms.com


THE CLINICAL SERVICES JOURNAL is published in January, February, March, April, May, June, August, September, October and November by Step Communications Ltd, Step House, North Farm Road, Tunbridge Wells, Kent TN2 3DR, UK.


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AI and the indispensable human in diagnostics


The growth of Artificial Intelligence (AI) in healthcare has led some to question whether its prevalence will eventually make humans redundant. However, most agree that it provides a means to support humans, rather than to replace them. Indeed, in diagnostic areas such as radiology and pathology, one of the key benefits of AI is its ability to automate repetitive tasks, enabling staff to prioritise on serious cases. “People might think of man vs machine scenarios, where computers will take over the prediction and identification of cancers and other illnesses altogether,” Chris Scarisbrick, Sectra UK & Ireland, told The Clinical Services Journal. “A peak of inflated expectations has emerged, as Gartner might describe it in its Hype Cycle for Emerging Technologies. When we start to come down from that peak to look at the low hanging fruit, it becomes clear that AI and the associated possibilities for automation, can make a more mundane, but nevertheless more immediate and positive difference to the productivity of our radiologists and pathologists.” With an urgent need to respond to growing volumes of work, rising masses of imaging, and the fact that there are simply too few professionals to cope with escalating demand, Chris believes AI offers opportunities to avoid costly delays in diagnoses that could significantly harm patient outcomes, even in the context of modern healthcare pressures. “AI applications and algorithms emerging


now, mean that computing technologies are able to recognise abnormalities and flag those cases to relevant staff,” he observed. “This automation supports radiologists and pathologists, not only enabling the most urgent studies to be reviewed first, but more than that, allowing specialist staff to be alerted to the more complex cases that require their attention, whilst others might be dealt with by less experienced teams.” Diagnosis of a huge range of conditions are


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particularly well suited to AI assistance, in particular conditions which are more common, where potentially millions of images have been used to train algorithms through extensive machine learning. Many other, more specialist cases, are not yet suited to AI techniques, where it remains of crucial importance that they are visualised from the beginning by a professional.


“In either of these instances the radiologist or pathologist still performs a very necessary role, supported by technology that helps to ensure a greater level of consistency,” Chris noted. “These human in the loop interactions allow for the best in time efficiency and diagnostic accuracy.” Chris cited Ki-67 protein cell counting as a


JUNE 2018


strong example of AI in reality: “This very time consuming and laborious task, has been automated in parts of the world including Linköping and Utrecht, by applying an algorithm that within seconds identifies up to 1000 cells within a region of interest – the area that the pathologist needs to be concerned with. “The human is in the loop to fix any incorrect positives and negatives, but the algorithm in conjunction with the pathologist, reduces the time that would be spent manually counting cells, whilst ensuring the highest level of accuracy.” AI is advancing at such a pace it is far beyond what any single technology provider could ever hope to cover. Medical imaging technology suppliers must provide an open interface to give very clever people the opportunity to apply their innovations.


AI is advancing at such a pace it is far beyond what any single technology provider could ever hope to cover.


“Radiologists, and increasingly pathologists, are accustomed to working with a single harmonised user interface, where they have all the diagnostic information at their fingertips,” noted Chris. “If it is to be used and accepted, AI must become harmoniously available to users in the systems already being used – such as their picture archiving and communication system, so that they can access that AI functionality for imaging they are working with.” AI cannot make the human redundant. Instead it is a means to eliminate repetitiveness through automation and, in turn, to make sure professionals have the capacity to do those tasks for which they are indispensable.


Chris Shaw l Editor chrisshaw@stepcomms.com


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