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AI may be as effective as medical specialists at diagnosing disease

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AI-disease

AI disease

AI disease-A new scientific review has concluded that artificial intelligence (AI) may be able to diagnose disease as successfully as human healthcare professionals, but a lack of quality studies means the real potential of the technology is unclear.

Researchers carried out the first systematic review of existing research into AI in the health sector and published their findings in The Lancet Digital Health journal.
It focused on an AI technique called deep learning, which employs algorithms, big data, and computing power to emulate human intelligence.
This allows computers to identify patterns of disease by examining thousands of images, before applying what they learn to new individual cases to provide a diagnosis. Excitement is building around the technology, and the US Food and Drug Administration has already approved a number of AI algorithms for use in healthcare.
AI has been hailed as a way to reduce the workload for overstretched medical professionals and revolutionize healthcare, but so far scientific research has failed to live up to the hype.
Of the 20,500 articles reviewed, fewer than 1% were found to be sufficiently robust, said Professor Alastair Denniston from University Hospitals Birmingham NHS Foundation Trust, UK, which led the research, in a statement.
“Within those handful of high-quality studies, we found that deep learning could indeed detect diseases ranging from cancers to eye diseases as accurately as health professionals,” said Denniston.
“But it’s important to note that AI did not substantially out-perform human diagnosis.”
Using data from 14 studies, researchers found that deep learning algorithms correctly detected disease in 87% of cases, compared to 86% for healthcare professionals.
AI was also able to correctly identify those patients free from disease in 93% of cases, compared to 91% for healthcare professionals.
While these results are promising, the researchers say better research and reporting is needed to improve our knowledge of the true power of deep learning in healthcare settings.
This will involve better study design, including the testing of AI in situations that are the same as those that healthcare professionals work in.

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