- Artificial intelligence (AI) and machine learning tools are becoming increasingly common in healthcare and beyond.
- A new study compared AI tools to human radiologists and found that radiologists were superior to machines at identifying conditions from X-rays.
- The researchers reported that the more complicated the diagnosis, the more strongly human experts performed compared to AI tools.
Artificial intelligence (AI) is already transforming the way we interact with the world, from helping forecast hurricanes better than ever to providing financial tips.
But when it comes to reading your X-rays at the doctor’s office, AI’s may not be ready to replace the radiologists of the world.
That’s according to a new study published in the journal Radiology.
In the study, Danish researchers took a pool of 72 radiologists and four commercial AI tools and stacked them against each other to interpret 2,040 older adult (average age 72) chest X-rays.
About a third of the X-rays displayed at least one of three diagnosable conditions: airspace disease, pneumothorax (collapsed lung), or pleural effusion (also known as “water on the lung”).
Researchers report that AI tools were reasonably
However, researchers said these AI tools also produced a high number of false positives, with their accuracy lessening the more complicated the diagnosis became. This was especially true in case cases of multiple concurrent conditions or when X-ray evidence was smaller.
For pneumothorax, for instance, when these false positives were added up, the positive predictive values for AI systems were between 56 percent and 86 percent. Radiologists, on the other hand, got it right 96 percent of the time.
Positive predictive values for pleural effusion were similar to those for pneumothorax, ranging from 56 percent to 84 percent…
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