{"id":33434,"date":"2025-01-17T18:48:06","date_gmt":"2025-01-17T18:48:06","guid":{"rendered":"https:\/\/peraltafinancing.com\/alternative-medicine\/is-ai-replacing-human-radiologists\/"},"modified":"2025-01-17T18:48:06","modified_gmt":"2025-01-17T18:48:06","slug":"is-ai-replacing-human-radiologists","status":"publish","type":"post","link":"https:\/\/fivemor.com\/?p=33434","title":{"rendered":"IS AI replacing human radiologists?"},"content":{"rendered":"


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A report from the Osler Lecture: Artificial Intelligence in Imaging, given by Professor Fergus Gleeson<\/a> on the use of AI in medical imaging.<\/em> September 20, 2024<\/em>, Mathematical Institute, Oxford University<\/em><\/strong><\/p>\n

Q: Is AI replacing human radiologists?<\/p>\n

A: No. We are not even close.<\/p>\n

But why ever not? When I saw the title of this lecture \u2013 Artificial Intelligence in Imaging \u2013 I guessed the subject matter would be that the interpretation of imaging was being increasingly performed more accurately and efficiently by AI. After all, I thought, it must be fairly straightforward. I am a little nervous about AI taking over from clinicians, but imaging? Well, that would be a great use of the technology. After all, images are just pictures, they can easily be scanned, and any abnormalities easily identified. A slightly more sophisticated version of Where\u2019s Wally.<\/p>\n

It seems I was not alone in thinking this. Geoff Hinton<\/strong>, the \u201cGodfather of AI\u201d, said in 2016<\/a> that radiologists would soon be superfluous to requirements. It was \u201ccompletely obvious\u201d, he said, that within 5 years deep learning would be surpassing radiologists. The situation, he said, resembled the cartoon clip in which the coyote had run off the edge of the cliff, but hadn\u2019t quite stopped running. It was over for radiologists. AI would be taking all their jobs soon. His advice: stop training them now! (NB \u2013 that interesting clip was from 2016 and can be watched with a strangely satisfying sense of dramatic irony in more ways than one. Presently, in 2024<\/a>, Geoff Hinton has resigned from Google and is dedicating his time to warning about the danger of AI and speaking of his regrets around the part he played in its development)<\/p>\n

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Professor Fergus Gleeson \u2013 a self-confessed workaholic with kindly eyes and an open and engaging demeanour \u2013 revealing that AI is a bit more tricky than we\u2019d like it to be<\/em><\/figcaption><\/figure>\n<\/div>\n

Professor Fergus Gleeson<\/a>, a highly esteemed radiologist specializing in the thorax, also anticipated the rise of the computerized radiologist. He knows there is a desperate need for something to speed up the reporting of scans. When he arrived in Oxford in 1992, there was one MRI scanner and ten consultants. This year, 2024, there are nine scanners and 75 consultants. As the population ages, so do the numbers of scans. Up to \u00a3390 million is spent by the NHS in England on screening for lung cancer every year. (It\u2019s not just us. In the US a quarter of the 350m strong population had a CT scan last year.) And as a result, there are delays. Scans may take up to 3 months to be reported. A quarter of a million go unreported each month. In fact, the NHS spends over \u00a3100million outsourcing scans to get them reported. Politicians are pinning their hopes on AI to clear up the growing backlog, and money is being thrown in its direction to try and find out where to use it in the NHS. \u00a33.5 billion is invested in AI imaging, which is the lion\u2019s share (76%) of the budget for AI in healthcare in the UK .<\/p>\n

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Yes this image is AI-generated<\/em><\/figcaption><\/figure>\n<\/div>\n

Professor Gleeson was not particularly distressed by the prospective demise of his profession. Instead, he set about trying to help develop the AI which would improve the diagnosis of lung cancer, in particular. He started out full of optimistic enthusiasm. In the current Wild West that is the AI business environment, he licensed an algorithm, he got funding, all systems were go! Happy days! He got down to the serious work of researching beachfront properties in the Bahamas. Then, he began to hit snags.<\/p>\n

At this point, he quoted Menken: \u201cfor every complex problem there is an answer that is clear, simple and wrong\u201d. So, it was not working out quite as well as he had hoped. What were the difficulties? Well, some are too complex and technical to describe in detail. But there are many. So many. They just kept coming, and getting more and more complicated the more he explained them. But here is a selection:<\/p>\n