In a randomized trial, researchers used artificial intelligence (AI) to identify lung cancer. The latest study, which was released on Tuesday, discovered that AI-assisted Tool dramatically enhances the detection of lung nodules on chest X-rays.
Excerpts from the Study
Lung nodules, which are abnormal growths that appear on the lungs and are relatively common, frequently result from prior lung infections, but they can also signal lung cancer in a small percentage of cases. 10,476 patients who had their chest X-rays taken between June 2020 and December 2021 at a health screening facility were included in the study. The patients were placed into two groups at random; one group had its radiologists study its X-rays with an AI-assisted Tool, and the other group did not.
The study revealed “strong evidence that AI might truly help in interpreting chest radiography,” said Dr. Jin Mo Goo, a co-author, and radiologist at Seoul National University Hospital in South Korea.
“Although AI-based computer-aided detection software has been shown in numerous studies to enhance radiologists’ performance, it is not commonly used,” he continues.
The Increasing Use of AI-assisted Tools in Medical Imaging
When AI was used to aid in the detection of actionable lung nodules on chest X-rays, the rate of detection was greater (0.59 percent) than when AI-assisted Tool was not used (0.25 percent). The rates of fraudulent referrals were the same for the two groups. Dr. Goo mentions that nearly all of the enrolled people were included in the trial since it was carried out pragmatically, which is how it would be in a true clinical environment.
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The researchers intend to carry out a similar study with chest computed tomography, which will also determine clinical results and process effectiveness. This paper emphasizes the expanding usage of AI in medical imaging and how it may enhance the precision and effectiveness of diagnosis. With these encouraging findings, it is expected that AI-assisted tools will have a bigger impact on lung cancer early diagnosis and treatment in the future. The study’s findings were published in the Radiological Society of North America journal Radiology (RSNA).
