Would you trust a computer to diagnose your illness? 

Healthcare has come a long way thanks to human endeavour — but even occasional human errors can have disastrous consequences.

A misdiagnosis can mean undergoing unnecessary treatment; a misread scan can mean a patient is wrongly given the all-clear. Potentially life-altering or even life-ending mistakes can be made, even by excellent doctors.

So the news earlier this year that computer programs can detect breast tumours better than doctors was hailed as ‘a huge advance’ by researchers.

The study, published in the journal Nature, compared the results of mammograms analysed by doctors with the same images read by a machine that had been ‘taught’ to identify tumours.

Healthcare has come a long way thanks to human endeavour — but even occasional human errors can have disastrous consequences (stock image)

Healthcare has come a long way thanks to human endeavour — but even occasional human errors can have disastrous consequences (stock image)

When the computer was asked to read images from nearly 29,000 women, the number of missed cancers — known as false negatives — fell by 2.7 per cent compared with when a single doctor reviewed the scans, while the number of mammograms incorrectly diagnosed as abnormal (known as false positives) decreased by 1.2 per cent.

The machine was as good as two doctors working together — the current system for reviewing mammograms.

With thousands of women a year misdiagnosed in the UK, any improvement in the reading of scans would be welcome — and with an estimated shortage of more than 1,000 radiologists (doctors who interpret scans), using technology to do the work of two doctors could free up much-needed time for other tasks.

‘This is a huge advance in the potential for early cancer detection,’ said study author Dr Mozziyar Etemadi, an assistant professor of anaesthesiology at Northwestern University in Chicago.

However, more research is needed to work out how such a system could be introduced, he added.

Artificial intelligence (AI) like this — advanced computer software which not only carries out tasks but ‘learns’ from the results — is hailed by some as a panacea for the NHS, which is strained by increasing patient numbers and stalling recruitment and retention of doctors and nurses.

Last year, the Government announced a £250million AI laboratory that will bring together research to find solutions to common healthcare challenges.

‘The idea is that AI can take some of the workload so that doctors can spend more time with patients,’ says Sarah Deeny, assistant director of data analytics at the independent charity The Health Foundation.

It does look promising, and not just in the field of breast cancer diagnosis. Research shows AI could revolutionise diagnostic testing, predict the most effective treatments and improve how hospitals are run.

Another project by the UK tech company Brainomix, backed by pharmaceutical giant Boehringer Ingelheim, uses AI to interpret brain scans of people with a suspected stroke. The Brainomix program analyses CT brain scans in one minute (stock image)

Another project by the UK tech company Brainomix, backed by pharmaceutical giant Boehringer Ingelheim, uses AI to interpret brain scans of people with a suspected stroke. The Brainomix program analyses CT brain scans in one minute (stock image)

For example, it is helping NHS Blood and Transplant predict how much blood hospitals will need on any given day, resulting in 50 per cent less waste.

A trial, published last year in Nature, showed AI was better than specialist doctors at spotting lung cancer; it also boosted detection of the cancer by 5 per cent, while cutting the number of people falsely diagnosed by 11 per cent.

It can also identify skin cancers with the same accuracy as doctors, and was as good as humans at diagnosing more than 50 eye conditions in another study.

AI has also been developed to diagnose atrial fibrillation — an irregular heartbeat. And last year, University College Hospital in London came up with an algorithm to flag up patients most likely to skip appointments. Using records from 22,000 MRI scan appointments, the program identified 90 per cent of patients who would not attend, who could then be targeted with reminders.

Almost eight million appointments were missed in 2017/18, according to NHS figures, each costing the NHS around £120. Addressing the problem could save almost £1 billion — equivalent to 257,000 hip replacements.

Another project by the UK tech company Brainomix, backed by pharmaceutical giant Boehringer Ingelheim, uses AI to interpret brain scans of people with a suspected stroke — a blockage in the blood supply to the brain.

By correctly identifying where the blockage is and the extent of the damage, patients can be given clot-busting drugs within the crucial four-and-a-half hour timeframe, or surgery to restore blood flow to the brain, to give them the best chance of

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