Health: Artificial intelligence being trained to predict risk of developing ...

Artificial intelligence is being trained to predict whether someone is likely to develop oral cancer and may 'revolutionise' diagnosis, researchers claim Oral cancer risk is increased by factors including poor diet, tobacco and viruses  Diagnoses of oral cancers have risen by nearly 60 per cent in the last decade However, the evaluation of a patients risk of the disease is still highly subjective UK researchers believe machine learning could be used to help guide doctors

By Ian Randall For Mailonline

Published: 10:54 GMT, 2 November 2020 | Updated: 10:54 GMT, 2 November 2020

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The diagnosis of oral cancer could be 'revolutionised' by using artificial intelligence to predict whether someone is likely to develop the disease, experts have said.

Experts led from the Universities of  Sheffield and Warwick have teamed up to investigate how machine learning could be applied to aid doctors in early detection. 

Diagnoses of oral cancers — including those of the mouth, tongue and tonsils — have increased by almost 60 per cent over the last decade, team noted. 

The risk of such cancers is heightened by such factors as alcohol consumption, increasing age, insufficient fruit and vegetables, tobacco and viral infection.

Doctors evaluate the likelihood of pre-cancerous changes in the lining of the mouth — so-called oral epithelial dysplasia — developing into cancer using 15 criteria.

As this approach is highly subjective, however, there is considerable variation in how patients are treated following biopsy — and a more objective system is needed.

The diagnosis of oral cancer could be 'revolutionised' by using artificial intelligence to predict whether someone is likely to develop the disease, experts have said. Pictured, tongue cancer

The diagnosis of oral cancer could be 'revolutionised' by using artificial intelligence to predict whether someone is likely to develop the disease, experts have said. Pictured, tongue cancer

'The precise grading of oral epithelial dysplasia is a huge diagnostic challenge, even for experienced pathologists, as it is so subjective,' said clinical dentist Ali Khurram of the University of Sheffield.

'At the moment a biopsy may be graded differently by different pathologists, the same pathologist may even grade the same biopsy differently on a different day.'

'Correct grading is vital in early oral cancer detection to inform treatment decisions, enabling a surgeon to determine whether a lesion should be monitored or surgically removed,' he added.

'Machine learning and artificial intelligence can aid tissue diagnostics by removing subjectivity, using automation and

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