Artificial Intelligence Helps Radiologists Detect Bone Fractures

PARIS, March 31. (Benin News) –

Artificial intelligence (AI) is an effective tool for fracture detection that could help doctors in busy emergency departments, according to a study published in the journal “Radiology”.

Misdiagnosis or late diagnosis of fractures on x-rays is a common mistake that can have serious consequences for the patient. The lack of timely access to expert opinion (DeepL), as the growth in imaging volumes continues to outpace the recruitment of radiologists, only exacerbates the problem.

AI can help solve this problem by acting as an aid to radiologists, helping to speed up and improve the diagnosis of fractures.

To learn more about the technology’s potential in the area of ​​fractures, a team of UK researchers reviewed 42 existing studies comparing diagnostic performance in fracture detection between AI and clinicians. Of the 42 studies, 37 used X-rays to identify fractures and five used CT scans.

The researchers found no statistically significant difference between the performance of clinicians and that of the RN. The sensitivity of AI for fracture detection was 91-92%.

“We found that the AI ​​worked with a high degree of precision, comparable to that of clinicians,” says study lead author Rachel Kuo, from the Botnar Research Center, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences at Oxford. Importantly, we found this to be the case when the AI ​​was validated using independent external datasets, suggesting that the findings can be generalized to the general population.

The study results point to several promising educational and clinical applications for AI in fracture detection, Dr. Kuo notes. It could reduce the rate of early misdiagnosis in difficult circumstances in the emergency setting, especially in cases where patients may suffer from multiple fractures. It has the potential to be an educational tool for young doctors.

It could also be useful as a “second reader,” reassuring doctors that their diagnosis is correct or prompting them to review images before treating patients,” Kuo notes.

The researcher cautioned that research into AI fracture detection is still at a very early preclinical stage. Only a minority of the studies she and her colleagues reviewed assessed the performance of AI-assisted clinicians, and there is only one example where an AI was assessed in a prospective study in a clinical setting. .

It remains important that clinicians continue to exercise their own judgment,” says Kuo. AI is not infallible and is subject to biases and errors.

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Artificial Intelligence Helps Radiologists Detect Bone Fractures

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