First, the Covid Sputters, Now the Scanning Errors: AI in Health Care
May 28, 2020
Have you ever heard of the CSI effect? It mostly deals with forensic science, but another symptom is that computer “zoom” and “enhance” features actually produce crystal clear images. In reality, they do not. The Register explains that you will want a second opinion on your next medical scan in the article, “Don’t Trust Deep-Learning Algos To Touch Up Medical Scans: Boffins Warn ‘Highly Unstable’ Tech Leads To Bad Diagnosis.”
In short, AI algorithms used to enhance medical scans has led to numerous misdiagnoses. Many medical and AI professionals believe that deep-learning algorithms will cut down on time needed for medical scans, because the algorithms automatically improve image quality. Findings state the opposite as small details, such as tumors, are blurred or deleted from images. Another concerns is that static or other debris could appear on the scans.
“ ‘There’s been a lot of enthusiasm about AI in medical imaging, and it may well have the potential to revolutionize modern medicine: however, there are potential pitfalls that must not be ignored,’ said Anders Hansen, co-author of the study and an associate professor at the University of Cambridge’s department of applied mathematics and theoretical physics in Blighty. ‘We’ve found that AI techniques are highly unstable in medical imaging, so that small changes in the input may result in big changes in the output.’”
To discover the error, CT, NMR, and MRI machines were tested. It was discovered that even the finest corruption, i.e., a patient moving, ruined the image.
For the time being, it is better to rely on tried and true medical scanning processes and use the data generated to teach deep-learning algorithms. In order for anything to become standard operating practice in the medical or any other field, statistical procedures need to be better. This common sense observation does not apply to marketing, of course.
Whitney Grace, May 28, 2020
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thanks for sharing